{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "login success!\n",
      "logout success!\n",
      "输出[filltrade]可视化图表：\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "posit 154512;up 54.51%\n",
      "输出[line]可视化图表：\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "输出[line]可视化图表：\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "股价最大回撤10.13% 从2025-07-28 00:00:00开始从2025-08-01 00:00:00结束\n",
      "输出[line]可视化图表：\n",
      "输出[annotate]可视化图表：\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "资金最大回撤10.01% 从2025-07-28 00:00:00开始至2025-08-01 00:00:00结束\n",
      "输出[line]可视化图表：\n",
      "输出[annotate]可视化图表：\n"
     ]
    },
    {
     "data": {
      "image/png": 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7DylZTcEoYM2GRo4c6aqW0mvYsKFbjrZw4UIXMr3zzjvq0qWLO7Zo0SIXSlnoZJo0aaLly5enHbNwybfszpbozZs3L+1Y+uVzWT2WGau6soql9CcAAAAAAIBA8RzYqLiIMlJEIQWjgFU81ahR47jLLHi64oor3DI533V8FVEW8qS/jYVMYWFhOnDggDtmt/WxqqLt27dnerusHsvMCy+84Jb/AQAAAAAABFp8YoqKxW/T0TJVVEzBKai2V/vrr7/07bff6s8//3Tb3Fu/posuusjtQGb9dyIjIzNcv2DBgjpy5Mhxx3yXm1M9lplHHnnEVWL5Tlu2bMnW5w8AAAAAAJBVa3bHqUrIboWV8m7YFoyCKngaN26c6/1kTcCjoqJcHyZrOG5L4kqVKuWaiKcXFxenAgUKHHfMd7k51WOZsZDK16eJfk0AAAAAACCQVu6w4GmPilWsrWAVVMGT7fa2e/fuDEGQVSClpKSoVatWmjVrVtqxDRs2uJ5LFh4de8yalFeqVMl9farHAAAAAAAAgtma7XtUIeSAIkof384oWARV8NShQwd9+eWXevXVV/Xpp5/qkksuUYUKFVwj8XPOOcf1ZPrwww/ddW1Xu/PPP9/1eerZs6f++OMP/fzzz0pKStKQIUPUtWtXd73LL79c48eP15IlS3To0CG98cYbacesn5Q1MN+2bZt27drldsLzHQMAAAAAAAhm+7eu9X5RMniX2gWsuXhmLCRasWKFXnvtNe3YsUONGjXSV199pYiICHd81KhRru/TAw88oNDQUP3666/u8jJlyriwyvpBFS1aVCVKlNDo0aPdsaZNm+ruu+9Wy5YtXQ+nOnXq6Pbbb3fHevTooQkTJrjLTOfOnXXZZZcF7PkDAAAAAABkhfXDTty73vtNyWoKViEeG2kusnPnTs2bN09t2rRR6dKlMxyz5XcrV650lVMWQKW3fPlyV9l07rnnHtfHac6cOTp8+LA7ZrvlZZVVYFkvKms0Tr8nAAAAAABwuuyKPaq3XnpIgyPHKvTxXVJoWLbef3ZlHrkueAomBE8AAAAAACAQfl21W2vG3K0by6xUxH8XBG3mEVQ9ngAAAAAAAPDPVu6MU/WwPQoP4sbihuAJAAAAAAAgl1m5I1a1I/YpJIj7OxmCJwAAAAAAgFwYPFVM3RXUO9oZgicAAAAAAIBcJDE5VXv37FTB1MNSCSqeAAAAAAAAkE3W7Tmkip7d3m+oeAIAAAAAAEB2WbkzVlVDfMFTcFc8hQd6AAAAAAAAAMi6lTvidEbhA1J4lFSopIIZFU8AAAAAAAC5yIqdcTqj0P6g7+9kCJ4AAAAAAABy2Y521UL3Bn1/J0PwBAAAAAAAkEvsO5Sg3XEJKpu8I+j7OxmCJwAAAAAAgFxi1c44hSpVheO3U/EEAAAAAACA7O3vVC38gEJSk6USBE8AAAAAAADIxv5ObUod8n5DxRMAAAAAAACyy8qdcWpe9KCkEKlEFQU7gicAAAAAAIBcIDklVat3xalO5H6peLQUHqlgR/AEAAAAAACQC2zcd0QJyamq7NkllQj+He0MwRMAAAAAAEAusHJnrDsvkZg7drQzBE8AAAAAAAC5wModcSpXLFIRMZulklQ8AQAAAAAAIBsrnpqULyAd3k3FEwAAAAAAALLPih1xOqtknPcbejwBAAAAAAAgO8QeTdK2g/FqXPiA9wIqngAAAAAAAJAdVu30VjrVCN8rhUVKRcsrNyB4AgAAAAAACHIrd8QqIixEZZJ2eBuLh+aOSCc80AMAAAAAAADBafPaZdr+2X/1WoFbtCe0bKCHk6/tO5yoWmWLKsx2tMsl/Z0MwRMAAAAAAMjUthkf6eykvzQsIlYf1xmu5NCCgR5Svta+Thlp6kapWjvlFgRPAAAAAAAgUyW3z9DmyDqqmrhJDycNly4bIYWEBHpY+ZfHI03cJDW7VrlF7lgQCAAAAAAATquYfbtUJ2mldta9TrrkbWnJ59KstwI9rPzt8F4p6XCu2dHOUPEEAAAAAACOs3b2d2oR4lG1s3pIlWtJO5dIPz0plWso1e4c6OHlTwc3ec9zUY8nKp4AAAAAAMBxUlf/pA2h1VTeQifT6QmpVmdpYl9p37pADy9/OrDRe2672uUSBE8AAAAAACADT2qqahycpV3l2v99YWiYdPkoqUhZafy1UkLcie/g0B5p3TRvTyJkb/BUqKRUMEq5BcETAAAAAADIYP2yv1RGB1W00QUZDxQqIfUaJ8Vul74aIKWm/n1s/3pp5lvSBxdIQ+tIYy6VNv5+2see54Onkrmnv5OhxxMAAAAAAMhg94LvVdETqTotzz/+YNm60mUjpXG9pCmPSJHFpZXfS7uXSeEFpVqdpIvfkn58XNr4m1SjQyCeQt7t8VQi9yyzMwRPAAAAAAAgg+Jbf9HqImeqWcHCmV+h3gVSp8elac94l33VvVDq+LC36XiBIt7rrPxB2jTztI47X1Q8RZ+p3ITgCQAAAAAApImL2a+6Ccs1v/ZDJ79ih/ukehdKZepKYRHHH6/eTpr6tJScIIVH5th4842UJClmW65qLG7o8QQAAAAAANKsnf2DIkJSVLllz5NfMSREKn9G5qGTqdZWSj4qbZufI+PMd2K2Sp6UXNfjieAJAAAAAACkSVz1o7aERKtSzQb/7o4qNJEKFJM20WA82/o7mVzW44ngCQAAAAAAOJ7UVFXbN1PbyrT793cWGiZVbUOfp+zs7xQSKkVVUW5C8AQAAAAAAJzNqxeqgvaocMOu2XOH1udp82xvfyL8Owc2ScUrSeEFlJsQPAEAAAAAAGfHvO901BOhumddmD13WK2dlHRY2rE4e+4vv0o8Iq2a7G3knssQPAEAAAAAAKfwll+1ulBTFSxcNHvuMLq5FFGYPk//hscjffdfb4+n/zyr3IbgCQAAAAAAKP5wnOrFL9aRqh2z705tx7sqrYO7z9PcD6SZb0nb5gXnksC/RkqLP5N6vimVb6jcJjzQAwAAAAAAAIG3evZkNQ1JUsUWPbL3jm25nQU7qSnehuPBJOGQ9P391lXdSou81VmVW0pVz/Y2Rq/cWorMpuqvU7H5T2nKI1Kb26XGVyg3IngCAAAAAAA6umKKdoSUVdU6TbI/ePrlOWnXMqliNt/3v7VtruRJkW79TUpOkDbP8oY9VmU0/SUpJEwqVkEqXEoqXPr40xmXSUVK58zY4nZJn/eRqpwldXlauRXBEwAAAAAAUPTemdpcqp0qhmZzV55KLaSwSGnTH8EXPFnIVLCEVL6RZM+7Siup3V1Saqq0b433eMxW6cg+7+nQbmn3Cu/Xh/dKa36Sen+e/eNKSZIm3CiFhEhXfOhdsphL0eMJAAAAAIB8btv6Zari2a4C9bpk/51HFPQuX7PgyQ9jx47Vpk2b0r6/4oortHTp0pPe5ujRo+rfv7/i4+Oz9iAWLNmSumPDNvu+bD2pRR+p02NS92F6ZEG0JhTpI90+S7p/tdTzDWnNFGnfOvnr+uuv16pVq9zX999/v+bPn+++/uqrr/TSSy9JPz4hbZ0jXfmRVKy8cjMqngAAAAAAyOe2zvlW5TxhqtOmW848QLW23ibetkObVfFkQe3atXXVVVfp1Vdf1YIFC7RkyRIXKoWHh+vAgQMqXLiw5syZk+E29957r3bs2KEnn3xSL7/8cqb3+/DDD3vDnfT+V7Vkt61QoUKmt9u3b5/CwtL1qGp0hfTTk9Ls9zSjaHddfvnlqlWrVqa33bp1q1544QUXOJmIiAgVKFBAgwYNUmxsrN544w01bNhQR44cUd2CB7Rr6gcq1vMFFa56lnI7gicAAAAAAPK5yI2/aHXkGTqjeMmceQDr8zTjZWnPKqlc/Szd5KyzztLUqVNdFdOXX36phQsXqnv37rrvvvuUkpLigpv0Bg8e7EKp77//Xs8//7z69u3rAp1ixYpluF5oaKgLn86oVEya9ox0zoNSmTp67rnn3LETsccsWrRoxkquFn2l2e8qom0XdevWTaNHj870tk899ZQLm8ytt96q//u//9P69ev1+OOPa/jw4brssstUpkwZDX3+Ka05uFCP7YzQJ5c0UzvlfgRPAAAAAADkYwlHj6jukQVaXOvWnHuQKq2l0HBp0+9ZDp6Sk5M1YMAA9ejRQ0OHDnVhTcGCBTVkyBAXMp177rnuelb9dOedd7rg5vXXX3eXPfroo/rkk0/UpEkT9enTR/369VPVqlXdMQuk3BK+Fd9LxQtI9c+SwgvozTffVFRUVNrj33DDDZo7d25awLV582ZNnz7dhU8ej0eHDh1S1/M66J2qRxWx/ue021nFlFVrmQULFmj//v3uawvFzNtvv+1CrEceecRVPDVq1Mjd98zff9PONYv0yd2N9eDSOmrXvr3yAoInAAAAAADymdiD+7Rp8QwdWveniu6crcYhCSp3Zvece8ACRaTo5tKmmVKr/lkKnS666CJdcMEFqlGjhrp27aoqVaq4vk8xMTF67LHHdMcdd+jKK690AdPAgQPdebt27bRo0SI1b95cqamp7vI9e/bo22+/1c0336wOHTq4JXPVq1dX/NYlij2UovJbh2WoTLr22mt1++236+OPP84wprPPPtuFYBZqZTDxJmnWl5KnrfvW7vv33393Xzdq1EiRkZHHPb/du3e78VeqVMlVdZly2qsIJepA+6dUYvsU5RUETwAAAAAA5HHxh+O0+IcRCt02R+Vil6pKylY1DvEoVoW1KbK+/qz3kM5q2CpnB2F9nhZ9lqU+T1YdZNVLTzzxhD777DMdPnzYBU4WRPl8+OGHaty4sR588EG3RO7uu+9OC3t8wY8FWCEhIWm9mWbPnu2W8F1x+eXa8PkCqWwTRbfrkRYOWWBlx4+1evVqd18TJkxwgVH6yiidNUD68TMpdrv71qqh0vMc833nzp21du1a/fzzz7rllltc2DV7ykQVWvyRKrdtq63xBVS+fO5uKJ4ewRMAAAAAAHmchU5nLXtaa8NqaWfJFtpVeYDKN2yvKrUbq3H6htk5qVp76Y/Xpf3rpdKZN+FOr0GDBlq+fLk7mddee831RypUqJBuvPFGF+jY0jvTqlUrtyTOQqYNGzaoffv27rgtaXv66af1n//8J+1+7XqNqpdTaNEjWh9VyYVRF198sWbNmnXCwMfCJuvHZMvm/vvf/7rQK02VVlLZ+tLyle5b6ynVpk0b93XRokWVlJSU4b6++eYbt5OdPQ+zduVybf/zC9WpVEWNOl7r+kRdcsklyitO3DULAAAAAADkCZ7dy7UptIpqPzFfZ935kVpfOlDV6jVT6OkKnYzt0BYSKm36I8s3seDIbNmyRe+++65rNG6VR1bBlD7QsSbitszOKp1saZ6dW1DUunXrDKGTryfU408+qXfnJkrFK7r+UOvWrXM7z9mSvvRsud4999zj+kNZOGX9oeLi4lyVUga2w92hXdKu5a6S6c8//0w7FTimCXqJEiUyPL9Phr+sX1cdkBpdqS5du7oKL1sSmFcQPAEAAAAAkMcVjV2rfYVrBHYQBaOkCo29fZ6yyHo6WUWS9V2y5t/Wq8mW0pUuXTpDdZIFTL/99ptrBu7z0ksvuQqp9KxBuQVXrasWVpOqJTV1xizXk+nXX39VfHx8hmVxkydPVtu2bV0/Jgu9fKz3kz2WLfuzJXMmuUo7TVmfqvbnne+qrY49ffDBB2khmklMTHTLAwukHtXvV8bp+fv6SUXLasaMGSpSpIi+++475RUETwAAAAAA5HHlEjYrsYR3p7WAsuV2G/+54skCINuJzoKjkSNHuuCmS5cubqc52ynOqpp69+6thIQE19vJqp2sEsmWsO3atct9v2rVKnf7Fi1auN3ojFVKWRPyZ84N100Xd3DXGzZsmLtfq5Dq37+/5s2bp9jYWL388stuWZ2FXxEREWljK1y4sKZMmeJ6QVmQZZI80uWdW+v3a1P1+4+TXMVV+lO/fv3SKrRefPFF77K+kkWVtHuVDpdrobuH/+iqut555x23tNCCrjVr1igvCPEc2+XqNNq7d69bh/nLL7+4hDG9hx56yP2wLc30Wbp0qStrs0TRJoNtoWjrN41NIttm0brVW4f5e++9N+12EydO1H333ef+J7/yyiu65ppr0o7ZNoa23tMSxVGjRqlTp05ZHr9NRGsoZg3Oihcv/i9/GgAAAAAAZL8D+/eq5Bu1NK/lULXofnNgB7PiO+mz3tJ/l0glqp70qkeOHHEhT7Y7GiO9WE26+C2p+XXZcpe2JC81dpfC32winfeo1P6eDMeTk5NdhZOdLCxz/agmPyTN/1i67Q95StV0YZs1UbceUVYRdewSvdMtuzKP0ECGTt27d9fGjRuPO7Z48WKX8lkHex/7H2PbFlpSaaVzFkpZwy1jYVPPnj1doGSpoaWRFmb5wipLQa0TviWSTz75pEs9jX1vaeiIESNc4mlhlm2rCAAAAABAXrFj7SJ3Xrp640APxbuzncnCcrscCZ3MljlWUyVV8TYA95flE9bHyfIHHwuUwktUlBpfKf01SkpJPm6XvtBQbwRjO+iFbPxd+us96fynXKN1K6qx4xY6mUCHTtkpYMFTr1693BrNzFJC207QmnfVrFkzw9pKS9msBK5WrVp6/vnn9f7777tjFjRFR0e7cKlOnTouXPIdsyqm8847z4VKts3iwIEDNWbMGHds+PDh6tOnj2sQZus27fyrr746bT8DAAAAAAByWszmJUr1hKhirUaBHopUuJRUrmGWGow/9thjrvjkoosucgUnJ/Pss89maPhtTci7devmltLZcjvfYq8//vhDzS+6Xm0/TNCkP5alXd9WSNnjWK8nn9WrV7veUZYXWMGK73oXXnih68VkxTK2FM8sWbJEHTt21DkvztbFI1YrfuHEtPtZsWKFW+1lgZWTcEj65nb1/bmYxqzy7mxnHnjgAZ1zzjnuMb/44osMz89Wf/myjBM9Z7Nt27bjVpRZkY79HGx8VgBkduzY4VZ8WZ8qWzK4bJn3Z/Hee+/pjDPOcNe1n5+vWsuWIlq2Yrv1WX+rXBE82RrNu+6667jLbR2j/Q+zH9SkSZNceZlZtGiRe4K+xLNJkyZpWyraMfsB+Jbd2f8kW5PpO5Z++VxWj2XGJomVmqU/AQAAAAAQzFJ3r9LO0PKKLFRUQaFau3/s82TFJzNnztScOXPcSiXrv3QiFtj88MMPGS4bNGiQC60saLIm5OPHj3eh0XXXXafx/erpl2cv0TPPPusailvuYKuorMdSetdff73rx2T38fnnn2vz5s1u97sbb7zRteyxXOP777931x08eLBrBzTjz3lqULOKPnrtaXd5YmKiK3h59+23FLlvufTncGnsFZowe6tiSpyh6/v0SVutZeGPBVpTp05NC7TMhAkTXCGOjedkz9lWd9ljHZtVrFy50vWZslDN17TcGrXbc7AeVVb88+qrr7rLLVSyXfXsur7nZtVdRYsWdSvLbOWZPXauCJ6sEdixDh065CaHVTpt2rTJPXHr/m4TwX5w6W9jIZM1BbNtEI89ZmsPt2/f7r4+1WOZeeGFF9z6Rt+pSpUq2fCTAAAAAAAg5xSJXau9hTJWwQR8ud3+dVLczhNexVrjWNscW35mhSYWQp3I7bff7sKTY29vVTrGqnx++uknF+xUio5WvZSViqzVzlUhWbDlWy1lQZXPwYMHXfWQFatY/vCf//zHhTH169d392ttg6w3tYVQpkKFCq4tkDU4XxRXUg3DN0nzPtITfbpIe9fol0FdtPL5DtJPg7T9QIIGTE5R3UbN3QouqygqVaqUtm7d6iq7/vrrL9WtW9fdr2UU1s/avvdd90TP2XIKC5bS92OyoGz9+vVplVQfffSRu9xWkVneYnbu3OlWkfmCJ3s8q4Ky52fKli3rqrYsQ7HlhVYRlWt3tfvyyy9dIy1L0SwttIlh/9OsnMzWQ9o6yPQKFizomo0de8x3uTnVY5l55JFHXMroOx2bhgIAAAAAEGzKHt2ohGDY0c6negcpJFRaPeWEV7EsoGpVb/NxC34sK/CnsCX97UuUKOECHHdZ2WJScrzr7+S73PopVapU6YS3T38fPhbAzJ49W5UrV05rJ2TVSm+88YZKVKqjJnWrad1HAzX6u981on9rXdb3LvWeXlkrL/1Zjy2trmuv76MHH3zQ9Zm21kBWlWXBkLUE8vWg9i03tDZF6a97ouds4ZflGulZ5mGrySxQsuomK/ZJ/7O0UOrjjz92OwNaRdjQoUNdddSff/7pwibToEEDN7633nrL3Uf6yqusCFcQsXTPltOVKVMmLRiyJXW2i13p0qVd6dmxE8EmiCWD6dd7+i43p3osM/Y/7NjwCwAAAACAYGVFExU9e7S7fH0FjaJlpertpWVfSi28S82OZVU76QMSXxuerPLd3j7jW5WQ9Xhyl+3bLoUXlCo2VXLyhLTeT//0+L77SN83yTZAsxVbtrztzjvv1Pz5811IZuHM41+MV8c2t+iCS+er2aMfu9t0npuoGTP/dFVW3377rcskLEiqXbu2C3+sL7UFQMaqkazaKrPr+qNixYoqV66c+9ruo2TJkm6FWcOGDV0FkwVm1iPbMhfj6wFlz8Mqm6ZPn67XXnvNPV/ri20/AwuirHrMVqHluoonSwptWV169gOx5NFK4NJ3jN+wYYPruWQ/uGOPLViwIC2tPNVjAAAAAADkdtvWLVZoiEclqjVRMLANxWwp2czkJpo5fZpm/vy9W0Z37Mk+69vSMvva+jNZyJH+uDUPP5mzzz5b06ZNc19bjyarELLAZPnajTparpkUXiDt8szYsjXfMrT092F9j3xL+Gw5nu96tizPqodSUlLcKq7QQsXV8Oz/aPWaNe4yC64sf7DgyEIfX89qq0SyyyzkWrhwofv52DI+a2xuzzmz6/rD+mhbnypjYZE1FbfnYY9nQZJVUvmW3Nlx63VlY7DCHOvtZOy6FqoZG6NVXvl6bGeJJ8BsCBs2bHBf792711O8eHHP8OHDPVu2bPG8/vrrnoIFC3o2b97sSUpK8pQtW9bzwQcfuOv279/f0717d/f1nj173PV++uknT2JioueCCy7wDBw40B1buHChp0iRIp7Fixd74uLiPM2aNfMMHTrUHfvmm288FStW9GzdutWzc+dOT6VKlTwTJ07M8thjYmLc+O0cAAAAAIBgM/PLtz2eQcU98bH7PcHAPnPb5+h/e3rssccy3O+HH37oGTRoUNr3y5cv99SpU8fz8MMPu8/68+fP93hSUz3PXVDK06lZDU+fPn08Z599ticlJSXtNnbZL7/8kvb9mDFjPC1btvTceeednrp167pMwa5/2223eVq3bu0555xzPL/99pu77rhx4zw1atTwFCpUyN3vxo0b3eXPP/+8u26DBg3c/aSmpnrWrl3r6dSpk6dNmzaeJk2aeObOnes5ePCgyziKFSvmKVeunGfIkCHu9pld90TP2adatWppXx85csRz6aWXeho2bOjG4Xt+jz76qCcqKsrTrl07d7LnZJ566in3c7PHsuzEftZLly71nHvuuS5bqVy5svu5+CPE/qMAspTMqpd82/1Zimgd623HOSsJs5IuK18zti7RyrsKFSrkGoxZYy9L/3wpnu2SZ53Wbe2lJYm2BtG3JtLWKdpaxzp16riU0O7Dnrollb5tCjt37uweI6vJnZWlWbpppYvpm3cBAAAAABAMfnv3btXf9a3KDlqvYGBVQlWqVdGhyoekjv9wZeujvdGW5lkDo/9dtkzSdLkKnObNm5/05lbdYzvEWfVTrVq1pP3rpTeaa1aDwdqsiq7i59ieSMdavHixlixZom7durmsIT+JzabMI+DBk7+szG3evHmuF5RvDaKPBVi2TWCHDh1cAJWelaZZ6du55557XB8nWzNppWN2zJ9yMYInAAAAAEAwm/PSRSqieDV86BcFi6eeekrPPP+MUu9KlYr5ccMUKfzdcF149oWa9M0k/x944Tjp6wHSQxulQiX9v30+E5tfg6dgQvAEAAAAAAhmGwc31L7y7dRiwEgFi7Sqp4aHpAv8uOEiSV9lrdopU5PukrbOkW7/u9czcj7z8Ku5uO0u98orr5z0OtYw68knn/S74zwAAAAAAMg+sYcPq3LqDoWVC6Id7SS3ZO2+e+5T6LxQKe4kV5wq6T1Jn9iTkUKnhapkqZK64447dNNNN7km2CdizcdteVy7du106623enek2zJbqnKWxowZo379+uXIc8O/DJ6SkpJcqGT9mKy3Utu2bV3H8//+978aNWqU24Huvvvuc0vhIiIi/LlrAAAAAACQjbauXabwkFQVr9pYwcZyhMKFCkt/nOAKayRtkXSzpLaSvpRSY1I14fMJblc7a5fz448/nvD+Bw0apBYtWrg+0tb/efxHo6Q9K/X6bwc0cuTIk4ZWyF7hWb3im2++qcqVK7ukcMiQIe5/8v79+902erZl4Pvvv69bbrlFZcqUcd/7tbUeAAAAAADIVgc3LXHn0bWbKtj4qp5cr6d2mfR6Wiup8f/KZap6Q6hy5cu5Sqa9e/e63ME2DzuRKVOmaOLEie7r7t27692XHtc1jaWe1/ZX04tSNHr06Bx+hvA7eNq8ebPb8c2W261bt05169Z1HeK3bt2qhIQENWnSRF999ZXGjRun22+/XR9//HFW7xoAAAAAAGSzxJ0rdFDFVaKEd8f3YKx6euXVV3Toj0x6PVn3nqh0O9mlSPfec6++/PJLt0GYZRBWHHMicXFxqlq1alrItX3zeunsCqrRtL02TZ+eg88Kpxw8vfzyy65EzRp4zZ07VyNGjNDs2bM1ffp0RUdHp13PksTzzz9f27dvz3A5AAAAAAA4fQoeXKPdkdVUQsHp76qnp5XazpOx6inS+v38bye738MVEhHiimEslzDvvvuuW5l1//33Z3rf1gzbVmrZrvbJSUnyxB+UqnaTWJ0V3D2ePv/8c33xxRe67rrrdNZZZ6l+/fpq3769q37ynaz3k50InQAAAAAACJzS8Rt1OKq2gpnr9VSwsDTzmANWzLRB0hIpeU+yypUrp9WrV7tldrbq6rffflNo6IkjjbPbnKVp496UfnhQfwzuohoFY6Xa5+f488G/CJ6+/fZb1zz8zDPP1CWXXOLOLT388MMPVaxYMVfqZv/zLX2cPHlyVu8WAAAAAABks0PxCaqauk2h5eopmLmqp3vvV+jckIw73NmwN0sh/xfiqpcee+wxd2ratKlKlSrl+k3bznamY8eO3tskHpZWfCt9NUB3FpqkR54YrEde+UCDp8Xp1kFvS82vC8yTzOdCPG5PwX92/fXXu3MLl6yBl52sj9PQoUM1YMAA/fXXX6pZs6Zr8JWYmOjK2fK62NhYRUVFKSYmxv1DAAAAAAAgGCxftkgNJ5yjDRd8ohpteiiYHTx4UFWqVNShxkelrukOzLMqGLmClxtvvDHzGx/YJK35UVo9Rdr4m5R8VCrXUKrfTTtKttbUpbt0dtu2qlWr1ul6OnlGbDZlHlnu8TRmzBgNHDhQ55xzjgYPHqyuXbvKMitLGK3ZuF1uzcbt3MyYMeOUBwUAAAAAAE7d/o2L3XmF2k0U7FzV03/v0zMvPafUtvL2erLeTrPCdWHPCzOGTinJ0pbZ0pop3rBpz0opNFyq1lbq9IRU70KptDdkqijpuuaBe17wM3gy1tvp999/d1sS2haGtsTu0ksvVaFChdKuk5qaqvj4eH/uFgAAAAAAZPOOdodVSEVKe3d2C3b/ve9+vTLsJR2ameyterLeTnuTNfipwd4rpKZI8z+Wpj0rHdkrFSkr1fmPdN6jUs3zpIKsQsr1wdNTTz2l8PBwvfXWWy50CgkJ0euvv67Nmze7ZXdpdxgerg4dOuTUeAEAAAAAwD8osH+1dhWoppq5ZBc3V/XU72o98+5YpZ7t3cnOqp2aN28ubf5T+uEBaediqem1Uuv+UsXm0kmaiyN4ZPn/UsGCBVWkSBEXOBUtWtSdbNvCTz75xPV0smN2Sk5Ods3Hs9g6CgAAAAAAZLNSRzbqUPHc1dfov4OGqXB4iDTmf9VO9w+UvrxF+qCrFBom3fSzdOlwqVILQqe8WPH08MMPu/MJEya4ZuIWRBlrKl6mTBnX/8knLi7ONSH3XQcAAAAAAJweRxKSVCV1qzaUDe6m4scqUaac7ru4hQZ/Nlc92p+h5jNulCIKST3flJpdR9iU13e1OxELmCIjI5UfsasdAAAAACDYrFi1Qg3GtdH6Lh+oZrvLlZscXDBJN/W+XM92KqwG3W6TOj4sFSoR6GHlS7Gne1e7E8mvoRMAAAAAAMFo74Yl7rxCreDf0e5YJZp20xejXpVqd5bKNQj0cJANshw8Wd8maxxup9ATlLelpKQoKSlJ/fr1U/fu3bNjfAAAAAAAwA8JO5YrQQVUuFxN5TrWy6nt3618kI+Cp2nTpunNN9886XVs1d6DDz6o559/PjvGBgAAAAAA/BS+f412RVRWVQtxgNwSPNmSuj59+vzj9QYPHqz69ev/23EBAAAAAIBTUPLwesWWyF072iHvynLwFBISkva1LaPbu3evW3JnVU62e90vv/xy3PUAAAAAAMDpE5+YosopW7SjTKdADwU49ebiy5Yt0+jRo93XFjxddtllp3I3AAAAAAAgG23cvEkNQuIUU/mMQA8FOPXgyaqazj333LTvLXwCAAAAAACBtWfDYtlecOVr5r4d7ZA3Zb49nZ9YXgcAAAAAQOAd3b5cyQpTkQp1Az0U4NQrnlJTUxUdHe2+ptoJAAAAAIDgELpvtXaHRys6vECghwKcevD0559/KiwsLK25eFJS0qncDQAAAAAAyEYlDq1XTPFa8paKALkoeLKA6cCBA+68QIECGZbZRUZGav/+/WnXsxPL7wAAAAAAOH2OJqWoUsoW7S/dOtBDAfwPnixYqlSpksLDw121U2YSExNd9dNbb72lO++8M6t3DQAAAAAA/qWN23aofsh+xVdqFOihAP4HTykpKVm9KgAAAAAAOEXLZ03W+j8n6YuoG22ZUZZvV/rgYg2VVLZm4xwdH5DjPZ4AAAAAAEDOiJ/5nrrH/aIj4SU0tcTlWb7d2WGr5FGIikU3yNHxATkePO3evVsfffSRHnjggUyPjxs3TldeeaVblgcAAAAAALLGk5qqanELdDi8pK46MEJXXXq5VLnlP99wy1/S6NHSmTdIBQqfjqECWRKqU2D9np588slMj/3111+6/vrrNXny5FO5awAAAAAA8q2t65epjA5q3dkvSNHNpQl9pSPezbxOKGabNL63FH2mdNHLp2uoQM4FT4ULF3Y72R3r4MGDuu6661y1U48ePU7lrgEAAAAAyLd2LPpZKZ4Q1WjZVbriAykhVvrmDttCPvMbJB6Rxl8jhUdKV3/iPQdye/BkoVNoaMabxsbG6qKLLlLlypX14YcfZtf4AAAAAADIN0I2z9T68FoqFlVKKlFVuvRdadUP0p/vHH9lC6MslNq7Rur1qVS0bCCGDGR/8HSsGTNmqEWLFqpfv75bYlewYMHsuFsAAAAAAPKVKjELtK9Mq78vqHehdPZA6acnpS1zMl55xlBp2ZfSpe9JFZuc9rEC2Ro8LVq0SNu2bdPhw4eVkpIij8ejWbNmqXfv3u70wgsv6IMPPsh0CR4AAAAAADi5HZtWqYL2KLJW+4wHzn/K2+9pYrp+Tyu+lX55Vur4qNSwZ0DGC2RFlredu+qqq7R27doMl7Vr107R0dH65ptvXMUTAAAAAAA4NVsX/KyKkmq26JLxQFiEdMWH0rvtpa9vlzo9Jn15q9TwYumczHebB3JdxdOvv/7qdrOzBuLLli1T0aJFNW3aNBdInX/++erbt68OHTqUs6MFAAAAACCP8mz8XRtCqyuqdPnjD5ao4l1St3qy9H5XqXRN6ZLh0jH9l4Fgk+UZWrFiRUVFRalYsWIqWbKkwsLC1LFjRw0bNkzr1q1TQkKCmjdvflxVFAAAAAAA+GfRMQu0u9RJVhPVu0DqcL9UqKTUa5xUoMjpHB5wSrIlGi1VqpQ+/fRTXXzxxercubN2796dHXcLAAAAAEC+sGf7RlX27FB4zQ4nv2LnJ6T/LvZWQAF5NXhKTk52zcWP9fLLL6tmzZq68cYbs2NsAAAAAADkC5sW/OTOq515/j9fOTQs5wcEBDJ4io2NdUvrjhUSEqK33npLP/74o8aPH58d4wMAAAAAIM9LWf+7NodWUpkKVDIhbzml4MmqmubOnZvpsTPOOEOPPvqo6/8EAAAAAAD+WfkD87SjBLvFI+8JP5UbRUZGqmHDhic8/vTTT/+bMQEAAAAAkG/s371N1VO3aG/1gYEeChA8zcWtz9NLL7103OWpqamaNWvWvx0XAAAAAAD5wqYFP7vzKlnp7wTkp13tPvzwQ23fvl0bN25Mu8xCJ2syDgAAAAAA/lnC2t+0PaS8yleuHeihAIFbatemTRsVLlzY7WZXsGBBTZ48WREREa7X0+23365q1arp8ccf16hRo3Tfffdl/0gBAAAAAMiDyu6fp21RZyo60AMBAhk82U52Fj6FhoZq2rRpGY4999xzOuecc9S7d28XRrVr1y4nxgoAAAAAQJ4Ss3+PaiRv0L5q/QI9FCCwS+2ioqJcQ3Hbtc4qn3ysAmrRokUaOnSoSpUq5SqfbAkeAAAAAAA4uQ0Lpio0xKNKTenvhLzplHa1Sy8xMVErV67Uww8/rLp166pkyZK67LLL1Ldv3+wZIQAAAAAAedTRNTO0S6UVXb1eoIcCBF/wFBMTo7i4OF1++eXaunWrXnjhBXXq1Ek9evTIvhECAAAAAJBHldo7R1uKN1f50H+19xeQN4On+Ph4ffPNNzp69KiWL1/uekD98MMPrvIJAAAAAACc2KHYA6qZtFbzqvQK9FCAHPOvItUKFSropptu0rXXXqsaNWro6aefVuvWrfXee+9l3wgBAAAAAMiD1s+fpvCQVFVo0jnQQwECX/G0ZcsWff311woJCdG+ffvcZampqa7ayfo82ddly5bVggULcm60AAAAAADkEYfXzNA+RalqnSaBHgoQ+ODpjjvuUKFChdzXXbp0cedr167VQw89lHadVq1a6ciRIzkxTgAAAAAA8pQSu//SpqJNVZr+TsjDshw8PfLIIxm+T0pKUvXq1bVq1aoMl5933nnauHGjOwYAAAAAAI539Mgh1UpcpQW1egZ6KECOOuVYNTQ0VMOGDTvu8q+++irLodPevXtdbygLqjJzwQUXaPTo0WnfT58+XQ0aNFCZMmWOe+yJEyeqWrVqio6O1rhx4zIce/vtt1W+fHnVrFlT06ZNy3DsscceU8mSJdWkSRMtXrw4S+MGAAAAAODfWLvgFxUISVHZRp0CPRQgOIOn5ORkdevW7bjLS5QokeXQqXv37icMncaOHaspU6akfb9nzx717NlT11xzjWbNmuWO//LLL+7Y0qVL1bt3bz3xxBPuNk8++WRaJZZ9f//992vEiBH65JNP1L9//7QeVdYE3U6TJk3Ss88+q169erl+VQAAAAAA5KS4Vb8pRkVUvUHLQA8FCL7gyYKfs846K9Nj1mT81ltv/cf7sJDHdsPLzP79+3XfffepXr16aZdZ0GTVTBYu1alTx4VL77//vjs2atQot8TPQqXGjRtr4MCBGjNmjDs2fPhw9enTRxdffLHatm3rzq0qy3fMQqkOHTq4UMseb8aMGafyIwEAAAAAIMsK7l2qzZH1FBoWFuihAMEXPFnQ07p1a/d1SkqKqxpK7+OPP/7H+xg5cqTuuuuuTI9Z6HTppZeqTZs2aZctWrTIhUu2q56xx583b17asU6d/i5PzMoxj8ejJUuWnPB2mUlISFBsbGyGEwAAAAAA/iobv16HS9QN9DCA4AuebCc7qz4644wz0i6zqqHPP//cVRJZ76fw8H/uWW69nTJjy+emTp2qIUOGZLjcQp70tylevLi2b99+yscOHTrkqrNOdLvMvPDCC4qKiko7ValS5R+fJwAAAAAA6cUfjlN06k6FlW8Y6KEAwRU8WVBz8803684779TDDz/sLgsLC3MnC3KsUumKK65w35+Ko0ePumV6tgSuWLFiGY5ZmBUZGZn2fcGCBXXkyJFTPuYLx050uxPt7BcTE5N22rJlyyk9TwAAAABA/rV1zUKFhngUVb1poIcCBFfwdPvtt6ts2bKuGil9YGNVTv369dPq1at17rnnnvJgnnnmGbVq1SrTpuWlSpVyDcZ94uLiVKBAgVM+VqhQIXc60e0yY8/ZqqLSnwAAAAAA8MfBjYvceeW6zQM9FCDH/fOaOEkrV67Ua6+95naDGz9+vOuzZNVPv/32mzu3He7sa+ub1KRJk7Q+TP769NNPXRDk2xnPqo9sCd9ff/3lAik77rNgwQJVqlTJfW3HrOH5TTfddMJjnTt3Pu5Yy5Yt3bFatWqlHUvf0BwAAAAAgOyWsnO5toWUV6WiUYEeChAcwdMrr7yiiRMnumDGt4wuMTFRDz30kAub4uPj9eCDD6Zd38KoU2HhlYVY6XtHWYPxG2+80X1/xx136Oeff3ZVVVZ11bVrV3f55Zdfrnbt2unuu+92PZveeOMNXXfdde6YLf0bMGCA+vbt65bX2U54r7/+etqxl156ye1ot3PnTvcc2dUOAAAAAJCTCh9cpd2FaslbEgHkbVkKnmzXupo1a6p9+/aaPHmyGjdu7PohzZw50x0vWbKkqxwyu3btUoMGDU5pMJUrV87wfdGiRVWmTBl3Mq+++qouuugid7lVRY0ePdpd3rRpUxc6WQWTjatOnTpuWaDp0aOHJkyY4C4zVvl02WWXua+tn9Q333zjHtd2rOvfv79atGhxSmMHAAAAACArKhxdr3WVegZ6GMBpEeKxkqUsmjRpkgYOHKgff/xRZ555ZlojbuujtHHjRleRZGHU/v37deDAgRwZ8IYNG9zSvw4dOrgAKr3ly5dr27ZtriLq2F5Nc+bM0eHDh92x9EsBrTrrjz/+cP2bWrdu7ddYbMc8293OGo3T7wkAAAAA8E9i9u9R1Bu1Nbfly2rZ/ZZADwfI8cwjSxVPPrYkLSkpyVUNdenSxV3m6/H01ltvKSUlRbNnz1bt2rWVU2wpnZ0y07BhQ3fKjPV6yow1RrcQCwAAAACAnLZ9zXxZZ6fSNdjRDvmDX8GTr5/Sn3/+6SqbrFjKwiZbgvfoo4+mXcd6PgEAAAAAgIxiNy1WkidMlWoTPCF/CD2VGz3zzDPasmWLxowZo4iICP3www9px6wCqk+fPtk5RgAAAAAA8obdy7UtrJIKRBYM9EiA4Kx4MtbAe/z48WkNu49dujZixIjsGBsAAAAAAHlKsdg12leklqoHeiBAMFY8TZkyJe1r22kusx3gduzYoXfffTd7RgcAAAAAQB7hSU1VdOIGJZaqF+ihAMFZ8XThhRe6nd+sx9PChQtVv359Pf300255nZ2s19Pvv//uAqoBAwbk3KgBAAAAAMhl9u3cojI6pIKVGgd6KEBwVjxVqVJFgwYNcl+PHj3a9XKy3ewSEhLcbne2u93IkSP11FNP5dR4AQAAAADIlXasne/Oy9ZsFuihAMEZPIWFhemss87S0KFD3W521157rdvZ7oUXXnAnC6CioqJcZRQAAAAAAPjb4S1LFO8poOgaDQI9FCA4l9pZyGTB08GDB7Vo0SKFhIS4k8/MmTPVr1+/nBgnAAAAAAC5WuieFdoaUU11wsICPRQguIKnQ4cOqXv37i5kmjZtmltm17FjR82ePduFUUuXLtXUqVP14IMPqnTp0jk/agAAAAAAcpkSh9bqYNHagR4GEHxL7SIiItSpUyft379f69ev1xNPPOH6O7355psujIqNjdWXX36pevXquWAKAAAAAAD8LTUlRZWTNimlTP1ADwU4rUI8VrKURbNmzdKtt96qxYsXa8+ePWrXrp1bdrd79+60pXZXXXWV5s+fr3Llyimvs8DNelrFxMSoePHigR4OAAAAACBIbVu/QpU+bqPFHT9Qk46XB3o4wGnLPPxqLl6tWjUXPs2dO1clS5ZM2+HOp23bturfv7+GDRt2ygMCAAAAACCv2bNugTuvUOfMQA8FOK2yHDwlJiaqc+fOWrVqlcaNG6frr78+bVe7nj17utMdd9zhluCNHz8+Z0cNAAAAAEAucnTbUsWoiMpWrBbooQDBuavdM8884yqazjzzTHeygOmaa67RG2+8ocjISHedAgUKqEaNGoqPj9e2bdtUqVKlnBw7AAAAAAC5Qvi+ldoWUUNRoX4tPALyT/B03nnnqUmTJmnfjxgxQrfccou6det23Fo/q3wqUqRI9o4UAAAAAIBcqvThtdpdsnmghwEEd3NxZERzcQAAAADAP0lMOKqQ56M1v+FDOuvqhwI9HCB4m4sDAAAAAAD/bF+/VBEhKSpW9e9VREB+QfAEAAAAAEAO2rd+oTuvVJcd7ZD/EDwBAAAAAJCDEncs026VUlTp8oEeCnDaETwBAAAAAJCDCu5fpZ0FawR6GEBAEDwBAAAAAJCDysav05GouoEeBhAQBE8AAAAAAOSQI4diFJ26S6EVGgZ6KEBAEDwBAAAAAJBDtq1ZpNAQj0pUaxrooQABQfAEAAAAAEAOObBxkVI9Iapct1mghwIEBMETAAAAAAA5JHXnMm0PLa/CRaMCPRQgIAieAAAAAADIIYVj1mhPoZqBHgYQMARPAAAAAADkkApH1+toyXqBHgYQMARPAAAAAADkgJh9u1RO+xURfUaghwIEDMETAAAAAAA5YNuaBe68dA0aiyP/IngCAAAAACAHxG1erCRPmCrVahzooQABEx64hwYAAAAAIO9ITknV8h2xmrPxgOZu3K/ua2doa1hl1YgsGOihAQFD8AQAAAAAyNeSkxK1cs5UbUkpqSOFK/t1W4+krQeOaO7GA5q/+YCOJKaoQHioLqoQpwv1h3ad9XiOjRvIDQieAAAAAAD5M2ya/X86vGCi6uz7RY0Uq0KpFXVB4ktK8vOjconCEWpZraTu6lxHraqXVKNKUYr8sq+UVEkVO92RY88ByA0IngAAAAAA+Sds+nOyDi/8Ii1s2qGyWl2hhyrUb6Oa0+/Wyh5blNrmdr/uNzw0RCEhIX9fsG2etPwb6eJ3pAiW2SF/I3gCAAAAAOQLi1+/Qmcemp4WNpVqfZXqNDtHFUP/t+/WoYUKm/GSwppeLRUte+oPNPVpqWx9qWmvbBs7kFsRPAEAAAAA8rzUlBTVi5utWZVvVJubXv07bErvvMekpROlac9IPd84tQda94u0/lfp6rFSaNi/HjeQ22XyLw0AAAAAgLxl+4YVKhJyVEXrnquQzEInU6S0N3ya/7G0faH/D+LxSD8/JVVuJdXv9q/HDOQFBE8AAAAAgDxv1+o57jy6fuuTX7FlP6lsPen/HvYGSf6wvk47FkrnPyWl7/kE5GMETwAAAACAPC9x20LtVimVLl/55FcMi5AueFHaPEta+kXWHyAl2btEr/b5UvX2/3q8QF5B8AQAAAAAyPMK71umHYVqZ+3Ktc6T6nWTfnpSSjyctdssHCvtWyt1fvJfjRPIawieAAAAAAB5XvTRtTpS6oys36Drs9LhPdIfr//zdZPipV9flBpdLlVs+q/GCeQ1BE8AAAAAgDxt784tKqsDiqzsRyhUqqZ09kBv8HRw88mv+9cI6fBub2NyABkQPAEAAAAA8rTtK/9y5+Xr/UNj8WN1uFcqWEL68YkTXyf+oPTbMOnMG6TStf7lSIG8JzzQAwAAAAAAICcd3rxQhzyFVLFaff9uGFlM6jJY+upWae4HUmRx6ci+jKe9a6TkBOmcB3Nq+ECuRvAEAAAAAMjTCuxZos0FaqlhWJj/N258lTd0+u4e7/dhkVLh0v87lZLK1JXOfUgqXjHbxw3kBQRPAAAAAIA8rezh1dpR+uxTu3FoqHT9V9Lhvd6wqUARKSQku4cI5FkETwAAAACAPOtwXIwqp2zXropNTv1OLGyyEwC/0VwcAAAAAJBnbVk5R6EhHpWs1TLQQwHyJYInAAAAAECeFbNhvpI8YapSr3mghwLkSwRPAAAAAIA8K2TnYm0Oq6rIgoUDPRQgXyJ4AgAAAADkWSViV2l/sXqBHgaQbxE8AQAAAADypOSkRFVN2qCU8o0CPRQg3yJ4AgAAAADkSVvXLlbBkCQVq94i0EMB8q2ABk979+5VjRo1tHHjxrTLvvnmG9WsWVPh4eFq1qyZVqxYkXZs6dKlatWqlUqWLKkHHnhAHo8n7dj06dPVoEEDlSlTRsOGDcvwOBMnTlS1atUUHR2tcePGZTj29ttvq3z58u4xp02blqPPFwAAAABw+uxdM9edV27QOtBDAfKt0ECGTt27d88QOq1bt059+/bViy++qG3btqlu3brq37+/O5aQkKAePXqoRYsWmjt3rpYvX67Ro0e7Y3v27FHPnj11zTXXaNasWRo7dqx++eWXtLCqd+/eeuKJJzRlyhQ9+eSTWrVqlTtm399///0aMWKEPvnkE/dY+/btC8jPAwAAAACQvZK3LdT2kPKKKlkm0EMB8q2ABU+9evXStddem+Eyq26y0Omqq65yVUi33XabFixY4I5NnjxZMTExrpqpVq1aev755/X++++7YxY0WTWThUt16tRx4ZLv2KhRo3Teeee5UKlx48YaOHCgxowZ444NHz5cffr00cUXX6y2bdu686+++uq0/ywAAAAAANmv6MEV2lW4TqCHAeRrAQueRo4cqbvuuivDZVYBdcstt6R9b5VJFiSZRYsWqU2bNipc2LsFZpMmTVzVk++YhUshISHu+9atW2vevHlpxzp16pR2n1k9lhmruoqNjc1wAgAAAAAEH09qqiolrNPR0jQWB/Jl8GS9nU4mMTFRr7zyigYMGOC+t5An/W0sZAoLC9OBAweOO1a8eHFt374909tl9VhmXnjhBUVFRaWdqlSpckrPHQAAAACQs3ZtW6+SilOhqs0CPRQgXwvaXe0GDRqkIkWKpPV4smbjkZGRGa5TsGBBHTly5Lhjvsszu11Wj2XmkUceccv9fKctW7Zk4zMGAAAAAGSXnavmuPMK9VoFeihAvhauIGS7y9luc3/++aciIiLcZaVKlXKNwtOLi4tTgQIF3DFrMH7s5b7bncqxzFhIdWz4BQAAAAAIPvGbF+iAiql8pZqBHgqQrwVdxdOGDRvc7nQWPDVs2DDt8latWrkd69Jfz3ouWXh07DFrSF6pUqVMb5fVYwAAAACA3KvgvmXaFllLIaFB97EXyFeC6l9gfHy8azBuu8tdeumlOnTokDt5PB6dc845rifThx9+6K5ru9qdf/75rs9Tz5499ccff+jnn39WUlKShgwZoq5du7rrXX755Ro/fryWLFni7uuNN95IO3bFFVfonXfe0bZt27Rr1y63E57vGAAAAAAg9yp/ZI3iSv5dzAAgMIJqqd2PP/7odqqzk+16l766qXr16ho1apSrhnrggQcUGhqqX3/91R0vU6aMXn31VV100UUqWrSoSpQoodGjR7tjTZs21d13362WLVu6Hk62S97tt9/ujvXo0UMTJkxI2zmvc+fOuuyyywLy3AEAAAAA2SPmwF5Fe3Zpe3TTQA8FyPdCPFZOlIvs3LlT8+bNU5s2bVS6dOkMxyygWrlypTp06OACqPQszLLKpnPPPfe4Pk5z5szR4cOH3THbLS+rrALLdrezRuO2Ix4AAAAAIPCWzfxBZ/x4jTZePU3VG7QI9HCAXCm7Mo9cFzwFE4InAAAAAAg+f376jJqtel3hj29XeMSJN5ACkPOZR1D1eAIAAAAA4N8K27VUmyNqEDoBQYDgCQAAAACQp5SOW6kDxesHehgACJ4AAAAAAHlJwtEjqpKyRarQONBDAUDwBAAAAADIS7asWqCIkBRF1aCpOBAMCJ4AAAAAAHnGgXVzleoJUZX6LQM9FAAETwAAAACAvCR1x2JtCaukIsWiAj0UAARPAAAAAIC8pPjBFdpTpG6ghwHgfwieAAAAAAB5wp6YI6qauFah0U0DPRQA/0PwBAAAAADIE2b++YeKhCSoTrNzAz0UAP9D8AQAAAAAyBO2LPtDqQpRsZo0FgeCBcETAAAAACDX27L/iKL2L9GhYjWlyGKBHg6A/yF4AgAAAADket8u3q5mYetVqHqrQA8FQDoETwAAAACAXG/ygk1qELJZEVVYZgcEE4InAAAAAECutmpnnEJ2L1O4kqXoMwM9HADpEDwBAAAAAHK1SYu26azITfKERkgVGgV6OADSIXgCAAAAAORaHo9HkxZt1wUltiqk/BlSeGSghwQgHYInAAAAAECutWDLQW3ZH68GnnVSJZbZAcGG4AkAAAAAkGtNWrhd1YumqlDMWqlSi0APB8AxCJ4AAAAAALlSckqqvlu8Q31rxShEHhqLA0GI4AkAAAAAkCvNWr9Pew8lqEvUNimiiFS2XqCHBOAYBE8AAAAAgNy7zK50YVU8vEKq2FQKDQv0kAAcg+AJAAAAAJDrHE1K0f8t3amezSopZNt8GosDQYrgCQAAAACQ6/y6ao/iEpJ1Sd1I6eAmKbp5oIcEIBMETwAAAACAXGfSom06I7q4aiau9l5AxRMQlAieAAAAAAC5StzRJE1dsVs9m0ZLtsyuUEmpZI1ADwtAJgieAAAAAAC5yo/LdikhOVU9LHjaPl+KPlMKCQn0sABkIjyzCwEAAADgdJn3zdvasX2LFkR1UkxE+UAPB7nAvE0H1Lp6KUVHFfRWPLXoE+ghATgBgicAAAAAAbNy0Z9qOv9xNQ/xqPuu4VoW0Ui/FTxPswp20KHQYqd8v00SFqioJ1azIjvIE8JCj7ymdJECuq1jLSl2m3R4t7fiCUBQIngCAAAAEBAJSclKmnSPdoZFq8I9vyp03U86Y8kEnbH+bQ04/K5U+3yp8RVS/W5SRKGs3WlygvTTIGn2cO/30VOkri9I1c7O0eeCAFk+yXtOY3EgaBH9AwAAAAiIaZ+/pcYpy5Vy4RCFFysrNbtWuv4r6b5VUtfnpCN7pS9ukl5vKv01UkpOPPkd7lktjeoszX1fuuBF6cYfJE+q9OEF0ud9pAMbT9dTw+mybZ5ULFoqViHQIwFwAiEej8dzooM4udjYWEVFRSkmJkbFixcP9HAAAACAXGPlxq0q9WE7HSjTUvXu/OLEV9y3TprxsrRovFSymnTeY1KjK6TQdH9Dt480C8ZIkx+SileSrvhAqtjEeyw1VVo8Xvp5sBR/QDr7dqn9vVJB3r/nCR/1kCKLS73GBnokQJ4Tm02ZBxVPAAAAAE6r5JRUrRz/qIqFHFWN3q+d/Mqla0mXvivdNlMqd4b05c3Su+2lVf/nDZziD0oTbpQm3eldlnfr9L9DJ2MBlVVS3TlPane39Odw6c0zpcWf5/jzRA6zUHH7Qim6eaBHAuAk6PEEAAAA4LT6YvIUXR7/rXa3fkjRpapk7UblG0rXfCptmSNNHSyNu1qqcpYUu0M6GiNdOVo649IT3z6yqNTpMe/uZz8+4Q2wdiySujwthYZl23PDabR/nZQQK1VqEeiRADgJKp4AAAAAnDZrd8Wq1pxBOlioiqK73uv/HVRpJfX5VrruS2/Fk1VE3fb7yUOn9KIqe5fiWQ+oP9+RxveWEg75Pw4E3rb53nMqnoCgRsUTAAAAgNMiJdWj78a+rv+GrFLiZV9J4QVO7Y5CQqTanb2nU719m9ukUrWkif2kDy6Qrhknlchi9RWCw/b53v+HhUoEeiQAToLgCQAAAMBp8emMJeodM1L7a3RTqbqdAj0cqe5/pJt+lD69WhrZyRs+VW6pPC1upzR9iBQSKhUu/b9Tqb+/tt3hipYL9Ci91WzWUL78GRl7dh1b8VTpzNM9MgB+IngCAAAAkOM27zsiz7TnVTw8UZGXvqygYb2jbp4mfdZbGt1NuuQdqdHlypNitnl3gTt6UCpWUTqyTzq8V0pNyni9Bj2kzk9JZWoHZpypKdL390nzPpRCwqQO90nnPJCxQi4lSdq5OOtLLAEEDMETAAAAgFOSmurR+r2HtGDzQS3evFedVj6lssk7tD2kgraHVtA2d15R20IrKCJ+r8aFTlHquU9KUZUUVIqWlW6Y5N0Zz5be7d8gnXO/8pSDm72hk4U6/adKpWr8XVmUeOh/IdQ+addSacbL0jtnSS36Suc+5P35nC7JCdKXt0grJkndX/NWaP02VFr5vTcUjG7mvd7u5VLyUSqegFyA4AkAAAABd+BwojauXqyYQ4cUV7xuoIeDk0j1eLRm1yEt3HJQi7YeVNzRZNcy6ZliX+ucxN+0snRnNUzYqbYJS1Q0cf/ft1OokkrWUmS7OxSUIgpKl43wNiuf9owUXlBqOzDQo5JSkqWwf/mx7cBGaXQPb2+rG7+XSlb7+5hdFlnMeypZXarcQmpytfTXe9KMV6RF46R2/5XOvl0qUEQ5ypq8f3adtGmmdNUYqUF37+X1u0lf3+5dDumrfrJldlYNVeEEy/AABI0Qj8cibpyK2NhYRUVFKSYmRsWLFw/0cAAAQD4WH39UcYke74fIIGZvPPfEJWjVzjit2hWnlTtiVWjHn7oi4Rt1Dp2vZIXq0eT+mphybqCHipMoU7SAmlUpoeZVS7rzZqlLVeTTS6ROj3lDgfRBgoUeBzZ4z2t19i5tC3Y/D5Z+HyZd/LbU/LrAjGH/eunHJ6S1U6UuT0utbz61f9/71kkf9fQuU7PdAG1Xv6w6sl+aMVT6a4RUpIy3Csz6QMXtkg7tzHgev1+qca7Uqr+3T5a/Y7XHGnuFtGe1dM2nUo1zMh5PTvT+P7FqrDL1vOOx29iOhgCCOvMgePoXCJ4AAEAwSEw4qr0vNNbGlDJ6IOlWbVPOLYupFrJTF4fO1EVhs7XBU0EPJd2sWBX1+37ClKLexRaqb8i3qpG4WrHFaulIiwEqtX+hCiweq8Sz71biuY97GyAj6BQpEKYQX7AQf0Aa3k4qWUPqM0kKDVOuZx+RvrtHmv+RdNXH3p5Hp8vRGG+48ue73ibf1dpKSyZItc+XLn5HKlY+6/e1d413eV2Bot7/N8WjT21MFhpOfUZaOtH7fVikdxxFK/x9XqCwtOxr6eAmqUJjqeVNUuMrpciiWes9NeZS73K/6774ezldZnYukb6+zXt+5g1SzzdP7TkB+EcET0GA4AkAAASDuT98oJZ/3aP4yLKKSDmiNWc+rh01Lsu26qcC8XtUbvMPKr/pW0XtX6zk8CLaF91RpXb+rqQCJbSkwzs6HFUnS/cVlnRINbd8qUqrPlJozBZvhUTbO70fqm289tZ01lveSg9bXmNLn3J6eQ9Onf3/+vwGacMM6bY//KumCXbWC+mL/tLK76TeE6SaHXN+SZ0FXb88JyXFS+3vkc4e6A101vzkXWrmSfEGLfZv45/sXil93FMqVNLbv8qfwOpErLLJKqcKlsj89SU1VVo3VZrzvrRmijfwatpLatlPKlUz8/u0flpW6aQQ6fqvstbQ3BqLLxgjVWsvlWVpLpBTCJ6CAMETAAAIBouf76gCngTVv+//pP97RFo4Vqp7odTzjVPbFt3eHtoyHwsTln8jbZju7aVSp4u3gqHuBd4Pw3ad8dd5KxwuGS417HnyD4rzRku/vujdUct2DbMP1SfaJn3VZGniTd5+O9d+duqVGshZ8z6Svr3LWxXU8GLlOba8a/w10qZZ3mVq1v8oJ9hyuimPSXtWSE2vlTo/cfyct93nrPn5qh+kM/tIF7xwfChr19n8p7R5lrc3k1UiWaWTLUsLRDNz+zc//2Pp8J6TX7dsfW/oxL9zIKgQPAUBgicAABBoG9csVfWx7TS/xQs6s8ft3gtt96dv75Y8qVL3V7MWCNiHRAuaNvwmbfxNit3mXeZWta3U5EqpQU+pcKnjb2c9fL653RtQWW+fjo9KoemWx9lbzRXfSj8/5Q2qml0rdXxEKlHln8dkS2k+7SWlJkvXjGP3qmBjvXhGnOsNIy3kzKsSD3uXge1dLfX9P6lc/ey77+0LpKlPS+umSVXPlro+f/J5bv+erCrKAuZiFaULX/KGOhY0WTi2b433elFVvD2SujwjFSmtgId39vxsCWFmbGmmVTwWKnG6RwbgHxA8BQGCJwAAEGi/vztQTXZ+qciHViuyUNGMlQ8WPtkyocZXecOnhFjpaOz/zmP+Pt++0Fu1ZEtdrAKpegfvh1b7IFwwC+9x7O3k7696P0DX7epdHlcwSto8W/rxcWnrX94PlucPlio08n9pj1Wc7FouXfZe3qyqyY1sy/tR53uXhN06Pe8vh7Q+Vh928573+7+Mu8KdCuu9NO1ZafnXUpm6UqfHveFuVpfH7l0rfXmztH2+999t+TOkqm28/2arnJW1YBcA/gHBUxAgeAIAAIF09Gi8Dr9YT+vLd1Wr20YefwV7m7f4M+mHB6WE/1Ub2BbxkcW9gZLv3Ja5WNhUvZ23H8ypsj40X9wkFSnrvU8LvazJsFVd1Drv1O/Xwg3rb7PsK6nbUO+uWQgsWxY2+z3p5qlSxabKF+J2Sh9c4K2AanOb1LKv//9eYrZ6l5su/NRbsdTxYanpNVJYuP/jseWrVjFVps6/+3cLACdA8BQECJ4AAEAgzfr2fZ09715tv3aaouuepPeMfVC28MaCJmsMnJNs6/bxvaXEQ1KnJ7zLsNIvvTtV1rR4yiPS7Hel8x73buueTc3T8yWbD3+84f1/U+4MqXxDKapq1v5frf1Z+uRy6T/PSW0HKl+x3demvygtGi+FRkhnXu8NoUpWP3nT8N3LpMWfS3+N9O7y1uF+b8PtiIKnc/QA4BeCpyBA8AQAAAJp4XMdVTgkQXUfnaWgYh+0zalUcZyMvW2dMVT65VnprNu8/XCyI9TKb47sl8b1knYs8lbAWbN3YzuQlWsglWvoPbeKmkO7vJU+6c9tiWatTlLvL/Lvz//Qbm+INGeU9+fXoId09p1S5Zbe/mhb50rb5kpb50k7FkpJR6QCxbxB3dl3SJHFAv0MAOC0ZR7Z/G4AAAAAp8PqlYvVLGmBFrd8UUEnuwMnH6twOvcBqXBJ6fv7pfj90sVvS2EROfN4eZFv6/r4g9KNP3gbWcftkHYt8552L5e2zffuiBYWKRUr790Zzc4rNPGe2xKxehfm39DJ2G6RnR6T2t/j/VnNelt63xpkl/T2gTLFK3t3wbNm+hZIVWzm3Q0SAPIZgicAAIBcaPu0Eaqowmpw/vXKd6zHU6FS0pe3eAOUK0fzgT4rLFD69Cpvtc1NP0qla3kvty3s7VSnS8bqMpYy/jObd61uklr0lVZP9jbqt55XFjQVqxDo0QFAUCB4AgAAyGUOHYlXo12TtLZidzUvmG4nu/yk0WXenfM+u8671f21n0kRhaQj+4457ZdSk6XStb1NmLPaxyivWT1FmnCjd/eza8ZLRcqc/PqETv6xOVW/m/cEAMiA4AkAACCXmf/TOJ0TEqOU829Tvla7s3TDJOnTK6WXa3kDpmNZA+iQUCklwfu99TQqXccbQtk29pVbee8nLwctcz+Uvr9XqnuhdPkoqsMAAKcVwRMAAEAuYvvCFFnysdZGNlTt2mcGejiBV6WV1H+qtOZHb3+dwqWlwqX+d17a2zDblo3FbpX2rpb2rvn7fNMf3h3KGl0hdR/mraDKS2wnQGvE/tsrUqubpQtfkkLDAj0qAEA+Q/AEAACQi6xYsUQtkhdoxZlB2FQ8UKxXUemTVH9ZNVOJqt5T7fMzHlsyUfruHundDtLl73uDrLzg0B7pq1ukdb9I5w+W2t2dt6u6AABBK6AL3Pfu3asaNWpo48aNaZctXbpUrVq1UsmSJfXAAw+4v+r5TJ8+XQ0aNFCZMmU0bNiwDPc1ceJEVatWTdHR0Ro3blyGY2+//bbKly+vmjVratq0aRmOPfbYY+6xmjRposWLF+fYcwUAAMgOO6aNUJwKq27nGwI9lLyh8RXSgN+8u5R90NVbHZSaolxtwwzp3XbSziXS9V9K7f9L6AQAyH/Bk4VO3bt3zxA6JSQkqEePHmrRooXmzp2r5cuXa/To0e7Ynj171LNnT11zzTWaNWuWxo4dq19++SUtrOrdu7eeeOIJTZkyRU8++aRWrVrljtn3999/v0aMGKFPPvlE/fv31759+9yx9957z50mTZqkZ599Vr169VJiYmJAfh4AAAD/JCbuiBrv+VYborsrLLJIoIeTd5SsLvWdLLW/R5r6jDTmEil2x6nfX9JRBYQFZr++KH18sbd/1YDfpVqdAjMWAAACHTxZyHPttddmuGzy5MmKiYlx1Uy1atXS888/r/fff98ds6DJqpksXKpTp44Ll3zHRo0apfPOO8+FSo0bN9bAgQM1ZswYd2z48OHq06ePLr74YrVt29adf/XVV2nHLJTq0KGDC7Xq1aunGTNmnPafBQAAQFbM/XmcyoUcVKXzBwR6KHlPWITU+QmpzyRv/6fhbaVlX0spSVm7fUKcNG+0NOI86bny0vv/kWa9I8Vs02kRt9MbOE1/STr3YemGb6RiFU7PYwMAEIw9nkaOHOmW2d19991ply1atEht2rRR4cLenTZs+ZtVPfmOWbgU8r8y4datW+vhhx9OO3bhhRem3Y8de/rpp9OOpQ+47JiFSzfddJOWLFniKqHSH5s3b57OP/+Ytf/pKrLs5BMbG+vOl79yoYoWpF0WAADIHkkhBZQQUlAJIZH/Oy+ohNCCOiP2D60v2FA1a7YI9BDzrhrnSAP+kCYNlCb08TYnt8uscshOpWr+vWzNWkJsnSPN/0ha+pWUHC/V7iJd8JK0/lfp50HSlEekKmdJDS+RGl4sRVXyv3pq5pvSn297xxJV+e9T8UpSVBXv435/vxQa7t3lr0aHHPnRAABwKgKWlljodCwLctJfbiFTWFiYDhw44I41bNgw7Vjx4sW1ffv2TG+XlWOHDh1SamrqccdWr159wjG/8MILGjx48HGXJxQooYgCEX7+BAAAADLh8SjCk6gSnkMqkLpPBVLjFek5qgKpRxURmqgDHYYGeoR5X5HSUq9PpR0LpXXTvA26/+8RKTXJ26DcAig7XzxB2rNCiqrq7aPU7FpvIGTaDJCOxkirJnsrp9KHUGf2kRpdJkUUOvEYLNRa9YP3cWO3Sy37SpHFpJit3tOW2d7LU5O917cxXTpCKlr29PyMAADIoqAq0wkPD1dkZGSGywoWLKgjR44cd8x3eWa3y8oxu9yc6HaZeeSRR3TvvfemfW+hVpUqVdT8znEutAIAAMhp3rpw5Diraopu7j11uM+7lG7jH/8LoqZJB8ZK9btJXZ+Tap4nhWbSwaJglNS0l/fkC6EWfyZ9c7s05VGpWW+pZT+pTO2Mt9uzWvq/h6V1U6VanaXrvpDK1Mm8p9OhXdKR/VK5hpmPAQCAAAuq4KlUqVKuUXh6cXFxKlCggDtmDcaPvdx3O3+PFSpUyJ3smC80Sn+7zFhIdWwwBgAAgHzAqo3qXeA9+UKf0LCs3z59CLV/vTT3Q2nBJ94ldDU7Sq36S9XaeXfVm/2ut3LqmvFS3QtOvCOdPX7xaO8JAIAgFVR/FmnVqpXbsc5nw4YNrqeShUfHHluwYIEqVfKukT/VYy1btjzhMQAAAOCE/AmdjmV9ov7zjHTvCunS96TEI9Jn10lDakpzP5A6PiLdPluqd+GJQycAAHKJoAqezjnnHLd87cMPP3Tf26521ujb+jzZrnN//PGHfv75ZyUlJWnIkCHq2rWru97ll1+u8ePHu2bh1rvpjTfeSDt2xRVX6J133tG2bdu0a9cutxNe+mMvvfSSe0zr7TRx4sS0YwAAAECOiijorYDq/5N0629Sl6elgXOkc+73HgMAIA8I8Xisc2EABxAS4iqbqlev7r6fNGmSrrnmGrcMLjQ0VL/++mtaU/F3331Xd911l4oWLaoSJUq4aqXy5cu7Y4899piGDh3q+jTVqVNHv/32m7sPe3o33HCDvvjiC3e9zp07u8ewx7Vqqosuukhz5sxxX/fv319vv/12lsdugVVUVJRiYmLo8QQAAAAAAPKM2GzKPAIePGVm586dmjdvntq0aaPSpUtnOGYh1cqVK9WhQwcXQKW3fPlyV9l07rnnHterycKlw4cPu2MWOvnYznZWSWW9m1q3bu3XOAmeAAAAAABAXhSbl4On3ILgCQAAAAAA5EWx2ZR5BFWPJwAAAAAAAOQdBE8AAAAAAADIEQRPAAAAAAAAyBEETwAAAAAAAMgRBE8AAAAAAADIEQRPAAAAAAAAyBEETwAAAAAAAMgRBE8AAAAAAADIEQRPAAAAAAAAyBEETwAAAAAAAMgR4Tlzt/mDx+Nx57GxsYEeCgAAAAAAQLbxZR2+7ONUETz9C/v27XPnVapUCfRQAAAAAAAAsl1cXJyioqJO+fYET/9CqVKl3PnmzZv/1f8E5K/E2ILKLVu2qHjx4oEeDnIB5gz8xZyBv5gz8BdzBv5izsBfzJngYJVOFjpFR0f/q/shePoXQkO9LbIsdOIfA/xh84U5A38wZ+Av5gz8xZyBv5gz8BdzBv5izgRedhTZ0FwcAAAAAAAAOYLgCQAAAAAAADmC4OlfiIyM1KBBg9w5kBXMGfiLOQN/MWfgL+YM/MWcgb+YM/AXcyZvCfH8233xAAAAAAAAgExQ8QQAAAAAAIAcQfAEAAAAAACAHEHwBAAAAAAAgBxB8AQAAAAAAIAcQfAEZDP69cNfzBn4izkDAACA3ILgCcgGixcv1sCBA93XISEhgR4OcgHmDPy1YsUKDR482H3NnAGQEwi14a/Dhw+7c+YO/MF8yX/CAz2AYLNq1SqNGDFCFSpUUKtWrdSxY8dADwlBbtGiRWrfvr3i4+PVtm1bXXvttYEeEoIccwanMmc6dOigIkWKuN9L5557bqCHhCC3Zs0affrppypRooSaNWvGnME/Wr9+vebPn68rrrhCycnJCg/nYwL+OXSy15ZnnnlGF154oQsT+MMITmbnzp0qV66cQkNDmS/5DL9RjvlrcvPmzd0L55QpU/Tbb7+5D4b2PZCZhQsXuuDgvvvucy+iGzduDPSQEOSYMzjVOWMVcvZhcPny5YQIOKlly5a5OdOlSxdt3bpVc+fOdX9Qq1evXqCHhiD20Ucf6fvvv3fB07GhEx8QkZnIyEh3fvvtt+vDDz90fxhhruBEbG4MGjRIqampeu+991z4ZF/bOfI+/i//j036V199VX369NFXX32lb775xv3SnTZtWqCHhiC1ZMkStWnTRg8++KD7S4+FlvbXZfsrM5AZ5gz8tWDBAhcg2JwZMmSIOnXqpM8//1y7d+8O9NAQpBITE/X444/r5ptv1sSJEzV27FhXxXLs6wzLHHCsbt26qXTp0i7gjo2N1f/93//pu+++c8cIEpAZ+6xkv6OOHj2qvn37us9PNlfs9YXXGBzL5oZVPH377be67bbb0kInO0feR/D0PzbpCxUqpKioKPd9rVq13Js2S+83bNgQ6OEhCNmbeeu38tRTT7kXTFvK0Lp167T5kpKSEughIsgwZ+CvYcOG6f7773dzxt7EN2rUSEWLFtXevXvdcd6s4VgFChRQ7dq1VbVqVSUlJbn3M/b9pEmT9NBDD+nNN9901/N9OAR8qlWrpnnz5rnfU88//7yrYvnvf/+rli1bateuXe46zBn4+N6z1K9fXxdddJHeeecdN1984ZMFmICP77WjYsWKrsXE/v37CZ/yGYKndOrWrev+MRh7sWzatKnKli2rI0eOHHddfvHixRdfdG/ifS+Y9mGwcuXKroTUhIWFBXqICDLMGfjr448/1tNPP522dKF69eqqVKmSHn30UXec8nRkxt7L2PK6119/3YUHVrnSsGFDN1+syvKee+5x16OKBenZ8m+rXvnpp59UpUoVzZw507WhsHlyzTXXuOswZ+Dje89y3nnnucDyrLPOcu9nfH8s6d+/v6uE4jMT0r922O+nzp0765ZbbtGOHTsIn/KRfP2Ode3atfrss8/csgVLXe+44w7deOONaaWj0dHRruT4999/T7vNnDlz3Dm/ePOn9HPG+mYYe6G0pQ3m4Ycfdn007DqAYc7AX1YB9+uvv7qwwCpWfL9zfHPm3nvvdX01/vzzT/c9b+qR/nXmwIEDbo6ceeaZroechZfWQsAqEV544QUXRFkPS/rL5W++OWPLMX2/m+x1xv7oaruuWn8w+90UERGhL774wi3VtHmD/Mv3u+nHH39M+91k7I9o9nvIquLsc9TVV1+tZ5991lVEFSxYMKBjRvC9zjzxxBNuWe8555yjAQMGED7lI/m2ufimTZvcm7Lrr7/e9V2ZPn26ypQpk7ZVtSX09mJZsmRJtxbV2Bs2a4T2119/ub8KIX/PGQskixcv7n652tIGq5KzN2h16tRxv5TtF6+hyWL+xZyBv9atW+eWYFp1waxZs9zyBVsmZUu/bc4Yq3iyN2affPKJ6xnmWzLFnMmfjn2dsQ+GVq3yyCOPuOObN2/O0Cja5s6WLVsyfHBE/p4zM2bMcDtm2vvcyy+/3H1QtGC7Ro0a7neUzZ9ixYq5r5E/nex3k73eWEWlLQG3uTR8+HBdd911+vrrr90fUC644IJADx9B8lnbdlm1HqfG/oB2/vnnu6/fffddt4GKLQWn+j/vyrcVT/bXnBYtWujtt992a5H79evnXlR79+7tjvsSelvXbl9bubqVj1piS+iUPx07Z6wRvf31x9YpG3tjZm/K7K/K1ozT3sAZPgzmX8wZ+OuXX35Rhw4dNGLECLfcxX4HzZ4921XG+dgHROu/8uWXX+qDDz5wlzFn8q9jX2duuukm9ybftzSqfPnyevnll7Vy5Uo3l+yDoPWz9PW0RP6T2e8mCyjt3MIF2zXTXlsmT56sVatWuZDbKuks9Eb+lNnvJvtDvG18YWzHTAsObEdEq2gZPXq0Ro4c6cIp5E/Hvs5YNdz69evT3gMb+4OaVVdaJa7t2GvLNJF35dvgyf7SZ2/A7EOgVTVZIvvSSy+5fk5XXnll2vUsdLK/Gtqbflvrbi+0yJ8ymzO2y1R8fHyGOWNLNJ977jlNnTpVcXFxLIPJx5gz8Jf9v1+0aJErPbdlLt27d3dv1uxD4X333Zd2PauSs4DBdl7NrA8h8vfrjAVNhw8fdtUI9uHP5pW9ubc/rtl1J0yYwB/R8rET/W6ythO+OWPvd21zg169erklnN9//72rbEH+lNnvJl9gaX+Yv+yyy9y8sv6D9sc0Y+9zCJ7yr6y+B7Y/wNqOvY899phbJo68K98GT7Y8oX379q6c2LaMtb8W219yrNTP/qH4Jn6TJk1c+ag1zSN0yt/+ac6k/1BoZcXjxo1zpelUIuRfzBn4q3nz5q6BuC3LtKWYttuqzaO77rpL27dvd9W3PvbGzQKGwoULB3TMCM7XGQsPbM5YddzPP//sdpyy+WNL8ayPD/KvE82ZUaNGuWDB2k4MHTrUHbf+YLYU3D40Iv860e8mC5lWr17tltVZLzBf6AT48x7YV/lEuJ235dvgySoM7B+DlZzbWmVf01br89S3b19Xpm5N8uzDoL1hs/AJ+VtW5oytZza2U5ntiIj8jTkDf9kfOGxralt2aSXpviWZFhTYjkHWI8EqWXx/GPHtxIr862SvM7ZrkC2LsfczPXr0cA1dq1atGughI4jnjFU8WZ8eawRsyzQtbChVqlSgh4wg/d1kv4dat26tpUuXurkC+PMe2CrmkH/ku+Apfad8W0/aoEEDV0ps4VJMTIxraGaNzmyd6YIFC1w6ayWlyL+yOmeWLVvm/uoDMGdwKnPGt8TSNrGoW7euW2Jnv4sSEhLcX5etwsn+2mzbmwNZfZ2x1xjrtQFkdc5YPzBeZ5CV301WcWu/m6yS0t7TAP68B7Yecsg/8tWudr5tGo01vrOmeJMmTXJrSq1ZnpUS24unbRlru9rRRBH+zhlCSjBn8G/mjPXHsA98trzlqquu0t133+16aVj17Zw5c9x1qT4ArzPwF3MG/uJ3E/zF6wxOypNPpKSkpH09ZMgQT8WKFT3ff/992mUTJ0703HbbbZ6qVau606uvvupJSkoK0GgRSKmpqe6cOQN/5w1zBv7KbM58++23aZcNGzbM06tXL090dLQ7ZtdJfxvkr99LhtcZ+Is5g6yIj49Pmy/8bkJW8bkJWZWng6fMXgBffvllT7ly5TzTpk1z3ycnJ2c4vmXLFs/evXtP2xgRPI4cOZJh3vheSJkzOJF9+/Z5Dh065ElISHDfM2fwT3bs2OE5evTocb+jjp0z6d+M2fxasWKFZ+vWrQEYMQJt2bJlnueee87NifQBFK8z+Kf3M8dizuBEFi1a5GnWrJl7vUmP3004kWPfy/AeGPkyeNqwYYNnwYIFx72xHzRokPuH8MsvvwRwdAhGixcv9nTu3NlzySWXeB5//HHPgQMH3OVPPPEEcwaZGjdunPtLn82bm266KW3OPPnkk8wZnNB//vMfT48ePdL+snyyOZM+ZED+ZO9lwsLCXHVBerzO4EQ2b97sueuuu9yHwvQhge/9jO/DIJD+daZo0aKeypUre/r27ZsWFJzocxO/m7B06VLPpZde6rnuuuvc76OYmBh3Ob+bcDJ5srn4N998o4suusg1LbN1pikpKe7y+Ph4jRkzRh07dgz0EBFENmzY4Lb8bNy4sdshat68eXrmmWfcMVt//PHHHzNnkMHcuXNdf4Onn37a7QB06NAht12sOXLkiD766CPmDDJ1+eWX67vvvnP9Dmyu2B+AbMexzOaMbW6B/Mt2iTr77LP10EMP6Z577slwzJqzfvjhh7zO4Dhbtmxx73Wtia/tOpZ+u3J7nTnvvPMCOj4EF9tIqV27dm5re9t9zH4v2euL2bFjR6bvgfndlL9Zf6a2bdu63Zht50vbjCD9e+DRo0fzuwmZCrH0SXnMa6+95prg2T+IsWPHqlWrVoEeEoLY+++/ry+++EI//PCDCynfffdd9wJq2wkDmXn11VddM81PP/3UNVK0EMp2HRsyZEjadZKTkzO86QfMb7/9pksuuUSlS5d2ocKoUaMUERER6GEhyNjvIpsnBw4ccDsZ2uvJ448/rqSkJDVs2NA1Zy1evDivMziO/ZG1R48eev75590f0yZMmKB9+/bp0ksvVcuWLQM9PASRtWvXqlmzZrr33nvdH9Jslzr7Q+yAAQN06623uj+MEDLhWPbHeduN7pNPPnHvgW3numLFiunll192v7ssuLTfVby3wbFC8+L2jTbRr732Wl199dXu3D4gpj8OpFe0aFH35j0uLs69WPbt21fr1693oSWQmRo1arg38nv27HFVlUWKFHFv7q3ScuDAge5y+zDIaw6M7+87dm5bUXfo0MH9ZXnnzp3q16+fO7Zt2zY3bwBjv4tsR6BNmza5HYHOOecczZo1y/2l2XaVsqoVq5TjdQbHvs7YH0Hs99KTTz7pKg/sj2oWMHTq1Ml9b5gzMDYv3nrrLRc6WWAQGRnpQif7fWTyYG0CsoG9j7HXEPv95NvB7ueff3aBt70P3r59u/ss7ltxBOSp4Mn3C9Q3+S29t+09rTz9sssuSwuf7Di/bGHSz4MmTZq4N/H2Zs0S+sKFC7s5tHfv3uNux4to/pV+znTu3Nm9vpQoUcKFB/v373eBk/2l0AKpG264QYcPH057TUL+njO+vxjbuZWlHzx40C1v+Prrr90btPPPP1/nnnuutm7dGuARI1jmjH3ga926tQuf7LXGgqjp06e7VgJvv/22qlSpoltuucUtB+d1Jn879nXGdO3a1S0Jt8usotuquC2IsurcdevWMWfyOd97WfusdOONN7o55JsTZ5xxht555x03f5gnyOw9cIMGDdzS3f/+97/q2bOnW8JrFf933XWXW23Uvn17V63rW7IJ5JmldtbHacSIES5ZtfWmVkZctWrVtBdRCw+GDh3qfvHashhbdpf+BRb5j2/O2F+KrfLA1iFbgGB8ZcW2pMH+suxbszxu3Dj3Rq5UqVIBHj0CPWfsF6q91liA4GPl6faXQvPXX3+5X74jR450fcOQPx37u+mss85SpUqV3GuMLWsoWLCgXnjhBVf5ZEuq7M2+zR3eqOVfx84ZW4ppyxeuueYaFzS98cYbacvq7HeTLXew+WNv9JE/HTtnLKy0+fDHH3+4CifrA2Z/fPWx98BXXHGFCzORP6V/P2O9nXy/m6zy337/2HtgCynt89NLL73kXoOQvx37ucleW6xCe/bs2XrzzTdd+PTII4+461oVlB0fNmyYLr744kAPHUEmV6cvVllgYYAtlbI38fYXZHuDtnz5chcs2Rv8MmXK6IEHHnANXfv06eNK1Qmd8q/0c8YqnOwvOt26dXNNXI1VPBkLmKxBp3nxxRfVu3fvTCugkP/mzPz5810lpf0i9s0ZC518fw2yCjpfGIX86djfTQsXLtRVV13l5oy9qbew26rkbAnVdddd5wIE+wv0nXfeGeihI4jez1gfJ7vc/nhmzejT93KqVq2ae43x/c5C/nOi15klS5a4QME+/FkwuXnz5rTbWEW3nZA/Hft+xjdn7HOTvb5Y+GQs9N64cWPa+2Cq/fOvY+eMrSCyz02JiYku1LYVALaRgW/u2CoAa11ix4Fj5eqOlDaxy5Yt696sV6hQwQVNUVFRrhfC1KlT1bRpU3eZNXG18Ml2nrLrWqNO+6BIw7z8J7M5Y6m8fRD0zRljfzW0vxjaB8Jnn33WvdDammbkPyd6nbGlUb45Y2/OrGm0fRC0r+0Xr/0FEflTZnPGGkHbnPnpp5/cX5htOaZV4dprjJWr23WtZw/yp8zmjDVqtd9FNmfq1avnPiRaPzlrHm095exrX7Uu8p8Tvc5Y4DRz5kxX1WTV21YpV6tWLffHs8WLF7vKBeRPJ5oz6T83mQsvvND1A+vVq5ebM1Ti5l+ZzZlXXnnFVT7ZJkzWKuCOO+5wVbkWTtnvK8PGXsiUJxfbsWOHp2jRop4PPvggw+Uvv/yyp1ixYp7FixdnuHzfvn2eXbt2neZRIjfOmdmzZ3tCQkI8kZGRnrlz5wZotMgNc2bZsmWejRs3eu655x5P8+bNPV27dvXMnz8/YONFcM+ZEiVKeDZs2OAZNGiQ55VXXnGXJycnB2ikyA1zxi5fsWKFZ8yYMZ5GjRq515kaNWrwOpPPnWjOvPTSS56SJUt6tmzZ4pk5c6b73XT22Wd7rrrqKs/ChQsDNl7krs9NO3fu9HTs2NGzbdu2AIwUueV1xo5//PHHnjPPPNNTu3ZtT4sWLTyLFi0K2HgR3HJt8JSSkuLO77//fk+PHj088+bNy3D86aef9jRp0sSzdevWAI0QuXXO2Ju1vXv3enr16uXe7CP/ysqcadasmWfPnj3u+yNHjrgT8q9/mjMWONmcsfAJyMqcGTx4sHtTb68tmzZt8qxfv9692Uf+lZXXGQsofb+bjh496k7Iv/z93GTXP3z4cEDGitwxZ5588kkXNMXFxbl5Y3+E9b3mAJnJ9c2OrNeK9Wyy7YWtGbSxQK1///6uNNCWSAFZnTPWE2zevHlueaaVo9evXz/Qw0WQz5mSJUu65bvG1r/bCTjRnLGdyKyHnC2bArIyZ26++WbX4PfHH390m6fUqFHDLXkATjRnbr31VrcM0/e7ydpL+DbAQP6W1c9Ndh36geFkc2bAgAHud5Mt07T2EtZ70D5HASeSK4On9LvSWa8V2w7UminaemTrsG+9mypWrOj6IBA8wZ85Y1tTWwN6Y2uVkX9ldc5YXydeZ5DVORMdHe1eZ5gz8Od1xpqI2/cAv5vgLz43IafmjDUR53cT8mxz8fT/EKwp67vvvqsVK1aoZs2amjhxotvOsVmzZu4vPXa5NVZE/naqc4bm8/kXrzPwF3MG/mLOwF/MGfiLOQN/MWeQYzxBLn2/FN9aU19Ts4oVK3qmTJmSdpmtLf3+++89nTt39nTp0sU1QmNNe/7DnIG/mDPwF3MG/mLOwF/MGfiLOQN/MWdwugR18GS7b5x//vme7du3e1JTU9MuHzJkiKd8+fKeadOmue/THzNJSUnuhPyHOQN/MWfgL+YM/MWcgb+YM/AXcwb+Ys7gdAra4GnBggVuK3vbmSO9t956y1OqVKm0fwiAD3MG/mLOwF/MGfiLOQN/MWfgL+YM/MWcwekWYv9RkFm7dq0aNWqkBx54wK0tNcnJyQoPD9eCBQt0+PBhtW/fPtDDRBBhzsBfzBn4izkDfzFn4C/mDPzFnIG/mDMIhKBsLv7dd9+pcuXKaf8QbBvHQ4cOuV3GbIvYrl27um0cDQ2gYZgz8BdzBv5izsBfzBn4izkDfzFn4C/mDAIhKCueTJs2bVwSu2nTJkVERKhLly7au3evhgwZolGjRqlPnz6BHiKCDHMG/mLOwF/MGfiLOQN/MWfgL+YM/MWcQb6teNq9e7eSkpKUkJDgtmucMGGCrrjiCh04cMCV/BUpUsRdLzo6Wvfff7/OPPNMNW7cONDDRgAxZ+Av5gz8xZyBv5gz8BdzBv5izsBfzBkEWqiCwMKFC9WyZUuXtF555ZX65JNPVKVKFV199dVq1qxZWqmf6d69u6KiorRx48aAjhmBxZyBv5gz8BdzBv5izsBfzBn4izkDfzFnEAwCXvG0b98+XXzxxbrlllvUoUMH/frrr3rzzTfVtm1bXX/99erXr59bb+pTsmRJFS9eXKGhQZGZIQCYM/AXcwb+Ys7AX8wZ+Is5A38xZ+Av5gyCRXgwlP2VKFFCAwcOdOfly5fX5MmTXTJrjc7MihUrNGvWLFceaF/v2LFDTZs2DfTQESDMGfiLOQN/MWfgL+YM/MWcgb+YM/AXcwbBIuDBU+nSpd3JGpvZP4b69eu7NaVjxoxJ+8cQHx+v6dOna9u2bUpMTHT/WKwTP/In5gz8xZyBv5gz8BdzBv5izsBfzBn4izmDfB08xcbGKjw83G3PWK5cOVf6l35y21rT5cuXp31v/zg++ugj93VcXJyKFSsWiGEjgJgz8BdzBv5izsBfzBn4izkDfzFn4C/mDIJRiCd9N7HTYMmSJerfv79LXqtVq+a2cvRt15iSkqKwsDB3nauuukqzZ892a0wHDRqkqlWr6qabbjqdQ0WQYM7AX8wZ+Is5A38xZ+Av5gz8xZyBv5gzCFqe0yghIcHTpUsXz1133eVZtGiR59dff/XUq1fPc99992W43vLlyz1RUVGe2NhYz7BhwzwhISGe2bNnn86hIkgwZ+Av5gz8xZyBv5gz8BdzBv5izsBfzBkEs9O61M5K/pKTk9WgQQM1adLEXTZjxgx17NjRXf7aa6+5yyydteM333yzvvnmG82ZM0ctWrQ4nUNFkGDOwF/MGfiLOQN/MWfgL+YM/MWcgb+YMwhqpyPdOnDggCcmJsZ9fccdd3jatGmT4fiuXbs8Z5xxhjvmU6NGDU9ERIRnwYIFp2OICDLMGfiLOQN/MWfgL+YM/MWcgb+YM/AXcwa5QWhOB1uLFi1S69atdf7556tdu3Zq3769KlWqpGeeeSbtOtb07KefftJnn32mN9980132xBNPuO0crfkZ8hfmDPzFnIG/mDPwF3MG/mLOwF/MGfiLOYPcIkebi+/YsUONGzfWrbfequbNm2vixImaP3++rrjiCrel4znnnONK/EJDvfnXU0895W7z3nvvpTU/Q/7CnIG/mDPwF3MG/mLOwF/MGfiLOQN/MWeQm+Roj6dt27apYcOGeu6559z39evX10MPPeS665cqVUrTpk1z/yief/55dzw+Pt6tMU1ISFCBAgVycmgIUswZ+Is5A38xZ+Av5gz8xZyBv5gz8BdzBrlJji61sxR1586dWrdunfu+UaNGOnjwoBYsWKB7771XPXv2dKmsNTizr9966y2X2EZGRiokJCQnh4YgxZyBv5gz8BdzBv5izsBfzBn4izkDfzFnkJvk6FI7K+H7/PPPddFFF6lYsWKuzG/o0KFavHixPv7447QSv5EjRyouLs6tMe3QoYMiIiJyakgIcswZ+Is5A38xZ+Av5gz8xZyBv5gz8BdzBrlJji61s4lua0zTT+6qVatqxIgRbvLbPxD7h2D/CFq1apWTQ0EuwZyBv5gz8BdzBv5izsBfzBn4izkDfzFnkJvk+K52xyaqVapUcaV99g9h2LBhaeV+gA9zBv5izsBfzBn4izkDfzFn4C/mDPzFnEFukaNL7TJj60579OihWrVqady4cZo5c6ZatGhxOoeAXIY5A38xZ+Av5gz8xZyBv5gz8BdzBv5iziBYnfbgac+ePSpfvrwrDbSu+lb6B5wMcwb+Ys7AX8wZ+Is5A38xZ+Av5gz8xZxBsDrtwZN5/fXX1bVrV7flI5AVzBn4izkDfzFn4C/mDPzFnIG/mDPwF3MGwSggwVNqaqrrug9kFXMG/mLOwF/MGfiLOQN/MWfgL+YM/MWcQTAKSPAEAAAAAACAvI8oFAAAAAAAADmC4AkAAAAAAAA5guAJAAAAAAAAOYLgCQAAAAAAADmC4AkAAAAAAAA5guAJAAAgwCZNmqSQkBCFh4dnerKtsW+66aa06+/YscNd7mPHHv3/9u6eJa4tCgPwugiKASGgdhMk4FSZIoWFjYXgLxCnsDJNQPyoxCboP7CRFFbKWEriL5CA2EwKC4k2Vn4khY2VglF0DPuAc6/e3Ds2xzHwPHCYc/Y+bPZ0w8vaaz58yO6LxWK8fv06SqVSFAqFGBwcbMp3AgBI/v7FAgBAU7S0tERPT08cHh7+dv7du3f1oGl3dzeGh4ejVqtl4dJdEJXCqbRGa2trLC0txdDQUFQqlVhbW3vS7wIA8E8qngAAnkHw1Mhd8PTmzZuoVqvx4sWL2Nvby67R0dGYmJjIKp8ervWYtQEA8qLiCQCgydIxu0buAqRU2ZRCqIuLi+jr68vGjo+Ps+Apjae1Jicno6OjI05PT7OgCgCgWVQ8AQD8AcHTw3fa29vj69ev2VUul++99/Hjx2x8fn4+l/0CADyWiicAgCZLYdH379+jq6vrt/Pn5+cxPj5+byxVPL19+7be42l6ejq7v7m5qVdFpU8AgGYSPAEAPIPg6dWrV//bXPyhVPGU+jslU1NT9fGrq6v49OlT7OzsxPb2do67BgBoTPAEANBkt7e3j34nBUvX19f/mk+VTj9//oyzs7NYX1+v94EaGBjIZc8AAI8heAIA+IOCp8XFxVhdXY3e3t76Ubs0l0Knly9fxsnJSRwdHWUVVJVKJT5//pz7/gEA/ouD/wAATVar1Rq+kyqaktnZ2dja2opSqRRfvnyJjY2N6O/vj2/fvkWxWIzu7u4oFApPsGsAgMZUPAEANFkKlRo1Fx8bG6s/p0biqcdTZ2dnVu2Uqpzev38fP378iJGRkUf9Sx4AwFMQPAEAPIPgqVFz8bu+Tql/08HBQWxubmbPKWRaXl6Oubm5qFarsbKyko2nxuLpqF1aFwCgWf66fUxTAQAAno3Ly8toa2u7N7a/v58dtyuXy9lzqn5aWFiImZkZ4RMA0DSCJwAAAAByobk4AAAAALkQPAEAAACQC8ETAAAAALkQPAEAAACQC8ETAAAAALkQPAEAAACQC8ETAAAAALkQPAEAAAAQefgFFGSUMD3RhsYAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "输出[line]可视化图表：\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import baostock as bs\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import sys\n",
    "import talib\n",
    "\n",
    "class DefTypesPool():\n",
    "    def __init__(self):\n",
    "        self.routes = {}\n",
    "    # 注册绘图函数\n",
    "    def route_types(self, types_str):\n",
    "        def decorator(f):\n",
    "            self.routes[types_str] = f\n",
    "            return f\n",
    "        return decorator\n",
    "    # 发现绘图函数\n",
    "    def route_output(self, path):\n",
    "        function_val = self.routes.get(path)\n",
    "        if function_val:\n",
    "            return function_val\n",
    "        else:\n",
    "            raise ValueError('Route \"{}\"\" has not been registered'.format(path))\n",
    "        \n",
    "class MplTypesDraw():\n",
    "    mpl = DefTypesPool() \n",
    "\n",
    "    @mpl.route_types(u\"line\")\n",
    "    def line_plot(df_index, df_dat, graph):\n",
    "        # 绘制Line图\n",
    "        for key, val in df_dat.items():\n",
    "            graph.plot(np.arange(0,len(val)), val, label=key, lw=1.0)\n",
    "\n",
    "    \n",
    "    @mpl.route_types(u\"bar\")\n",
    "    def bar_plot(df_index, df_dat, graph):\n",
    "        # 绘制bar图-Volume\n",
    "        graph.bar(np.arange(0, len(df_index)), df_dat['bar_red'], facecolor='red')\n",
    "        graph.bar(np.arange(0, len(df_index)), df_dat['bar_green'], facecolor='green')\n",
    "\n",
    "    @mpl.route_types(u\"annotate\")\n",
    "    def line_plot(df_index, df_dat, graph):\n",
    "        #绘制annotate图\n",
    "        for key, val in df_dat.items():\n",
    "            for kl_index, today in val['andata'].iterrows():\n",
    "                x_posit = df_index.get_loc(kl_index)\n",
    "                graph.annotate(u\"{}\\n{}\".format(key, today.name.strftime(\"%m.%d\")),\n",
    "                               xy=(x_posit, today[val['xy_y']]),\n",
    "                               xycoords='data',\n",
    "                               xytext=(val['xytext'][0], val['xytext'][1]),\n",
    "                               va = val['va'], #点在标注下方\n",
    "                               textcoords='offset points',\n",
    "                               fontsize=val['fontsize'],\n",
    "                               arrowprops=val['arrow'])\n",
    "                \n",
    "    @mpl.route_types(u\"hline\")\n",
    "    def hline_plot(df_index, df_dat, graph):\n",
    "        #绘制hline图\n",
    "        for key, val in df_dat.items():\n",
    "            graph.axhline(val['pos'], c=val['c'],label=key)\n",
    "\n",
    "    @mpl.route_types(u\"filltrade\")\n",
    "    def filltrade_plot(df_index, df_dat, graph):\n",
    "        # 绘制filltrade 图\n",
    "        signal_shift = df_dat['signal'].shift(1)\n",
    "        # 最前面的NAN用-1填充\n",
    "        signal_shift.fillna(value=-1, inplace=True)\n",
    "        list_signal = np.sign(df_dat['signal'] - signal_shift)\n",
    "        bs_signal = list_signal[list_signal != 0]\n",
    "\n",
    "        skip_days = False\n",
    "        for k1_index, value in bs_signal.items():\n",
    "            if (value == 1) and (skip_days == False):\n",
    "                start = df_index.get_loc(k1_index)\n",
    "                skip_days = True\n",
    "            elif (value == -1) and (skip_days == True):\n",
    "                end = df_index.get_loc(k1_index)\n",
    "                skip_days = False\n",
    "\n",
    "                if df_dat['jdval'].iloc[end-1] < df_dat['jdval'].iloc[start]: #赔钱显示绿色\n",
    "                    graph.fill_between(np.arange(start, end), 0, df_dat['jdval'][start:end],color='green', alpha=0.38)\n",
    "                    is_win = False\n",
    "                else: #赚钱显示红色\n",
    "                    graph.fill_between(np.arange(start, end), 0, df_dat['jdval'][start:end],color='red',alpha=0.38)\n",
    "                    is_win = True\n",
    "                graph.annotate('获利\\n' if is_win else '亏损\\n',\n",
    "                               xy = (end, df_dat['jdval'].asof(k1_index)),\n",
    "                               xytext = (df_dat['xytext'][0], df_dat['xytext'][1]),\n",
    "                               xycoords='data',\n",
    "                               va = df_dat['va'],#点在标注下方\n",
    "                               textcoords = 'offset points',\n",
    "                               fontsize=df_dat['fontsize'],\n",
    "                               arrowprops=df_dat['arrow']\n",
    "                               )\n",
    "                # 整个时间序列填充为底色blue透明度alpha小于后标注区间颜色\n",
    "                graph.fill_between(np.arange(0, len(df_index)), 0, df_dat['jdval'], color='blue',alpha=.08)\n",
    "\n",
    "\n",
    "                          \n",
    "\n",
    "class MplVisualIf(MplTypesDraw):\n",
    "    def __init__(self):\n",
    "        MplTypesDraw.__init__(self)\n",
    "    \n",
    "    def fig_creat(self, **kwargs):\n",
    "        if 'figsize' in kwargs.keys():\n",
    "            self.fig = plt.figure(figsize=kwargs['figsize'], dpi=100, facecolor=\"white\")\n",
    "        else:\n",
    "            self.fig = plt.figure(figsize=(14,7),dpi=100, facecolor=\"white\")\n",
    "        self.graph = self.fig.add_subplot(1, 1, 1) #创建子图\n",
    "        self.fig.autofmt_xdate(rotation=45) # 避免x轴日期刻度的重叠\n",
    "        plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "        plt.rcParams['axes.unicode_minus'] = False \n",
    "\n",
    "    def fig_config(self, **kwargs):\n",
    "        if 'legend' in kwargs.keys():\n",
    "            self.graph.legend(loc=kwargs['legend'], shadow=True)\n",
    "        if 'xlabel' in kwargs.keys():\n",
    "            self.graph.set_xlabel(kwargs['xlabel'])\n",
    "        else:\n",
    "            self.graph.set_xlabel(u\"日期\")\n",
    "        self.graph.set_title(kwargs['title'])\n",
    "        self.graph.set_ylabel(kwargs['ylabel'])\n",
    "        self.graph.set_xlim(0, len(self.index)) #设置x轴的范围\n",
    "\n",
    "        if 'ylim' in kwargs.keys(): # 设置y轴的范围\n",
    "            bottom_lim = self.graph.get_ylim()[0]\n",
    "            top_lim = self.graph.get_ylim()[1]\n",
    "            range_lim = top_lim - bottom_lim\n",
    "            self.graph.set_ylim(bottom_lim + range_lim * kwargs['ylim'][0], top_lim + range_lim *kwargs['ylim'][1])\n",
    "        \n",
    "        if 'xticks' in kwargs.keys(): #x轴刻度设定\n",
    "            self.graph.set_xticks(range(0, len(self.index), kwargs['xticks']))\n",
    "        else:\n",
    "            self.graph.set_xticks(range(0, len(self.index), 15))\n",
    "\n",
    "        if 'xticklabels' in kwargs.keys(): #参数设置为日期\n",
    "            self.graph.set_xticklabels([self.index.strftime(kwargs['xticklabels'])[index] for index in self.graph.get_xticks()])\n",
    "        else:\n",
    "            self.graph.set_xticklabels([self.index.strftime('%Y-%m-%d')[index] for index in self.graph.get_xticks()])\n",
    "\n",
    "    def fig_show(self, **kwargs):\n",
    "        plt.show()\n",
    "\n",
    "    def fig_output(self, **kwargs):\n",
    "        self.index =kwargs['index']\n",
    "        self.fig_creat(**kwargs)\n",
    "        for path, val in kwargs['draw_kind'].items():\n",
    "            print(u\"输出[%s]可视化图表：\" % path)\n",
    "            view_function = self.mpl.route_output(path)\n",
    "            view_function(self.index, val, self.graph)\n",
    "        self.fig_config(**kwargs)\n",
    "        self.fig_show(**kwargs)\n",
    "       \n",
    "\n",
    "\n",
    "# 登陆系统\n",
    "def bs_k_data_stock(code_val='sz.000651',start_val = '2025-01-01', end_val='2025-05-01',freq_val='d',adjust_val='3'):\n",
    "    lg = bs.login()\n",
    "    # 获取历史行情数据\n",
    "    fields = \"date,open,high,low,close,volume\"\n",
    "    df_bs = bs.query_history_k_data_plus(code_val, fields, start_date=start_val, end_date=end_val,frequency=freq_val ,adjustflag=adjust_val)\n",
    "    #日K线，3，默认不赋权，1 后复权，2 前复权\n",
    "    data_list= []\n",
    "    while (df_bs.error_code == '0') & df_bs.next():\n",
    "        #获取一条记录，将记录合并在一起\n",
    "        data_list.append(df_bs.get_row_data())\n",
    "    result = pd.DataFrame(data_list, columns=df_bs.fields)\n",
    "\n",
    "    result.close = result.close.astype('float64')\n",
    "    result.open = result.open.astype('float64')\n",
    "    result.low = result.low.astype('float64')\n",
    "    result.high = result.high.astype('float64')\n",
    "    result.volume = result.volume.astype('float64')\n",
    "    result.volume = result.volume/100 #单位转换:股-手\n",
    "    result.date = pd.DatetimeIndex(result.date)\n",
    "    result.set_index(\"date\", drop=True, inplace= True)\n",
    "    result.index = result.index.set_names('Date')\n",
    "\n",
    "    recon_data = {'High' : result.high, 'Low': result.low, 'Open': result.open, 'Close':result.close, 'Volume': result.volume}\n",
    "    df_recon = pd.DataFrame(recon_data)\n",
    "\n",
    "    #退出系统\n",
    "    bs.logout()\n",
    "    return df_recon\n",
    "\n",
    "app = MplVisualIf()\n",
    "def get_trade_signal(stock_dat):\n",
    "    df_csvload_trade = pd.read_csv('600681.csv',index_col=None,parse_dates=[2,3])\n",
    "    stock_dat = stock_dat.assign(Signal = np.nan)\n",
    "    stock_dat.loc[df_csvload_trade[\"Buy-Time\"],'Signal'] = 1\n",
    "    stock_dat.loc[df_csvload_trade[\"Sell-Time\"],'Signal'] = -1\n",
    "    # 与前面元素保持一致\n",
    "    stock_dat.ffill(inplace=True)\n",
    "    # 序列最前面几个NaN用-1填充\n",
    "    stock_dat.fillna(value = -1, inplace = True)\n",
    "    return stock_dat\n",
    "\n",
    "\n",
    "def draw_trade_chart(stock_dat):\n",
    "    # 交易获利/亏损区间可视化\n",
    "    layout_dict = {'figsize':(14 ,7),\n",
    "                   'index':stock_dat.index,\n",
    "                   'draw_kind':{\n",
    "                       'filltrade':{\n",
    "                           'signal':stock_dat.Signal,\n",
    "                           'jdval':stock_dat.Close,\n",
    "                           'va':'top',\n",
    "                           'xy_y':'Close',\n",
    "                           'xytext':(0, stock_dat['Close'].mean()),\n",
    "                           'fontsize':8,\n",
    "                           'arrow': dict(facecolor='yellow',shrink=0.1)\n",
    "                       }},\n",
    "                    'title':u'600111 交易持股区间',\n",
    "                    'ylabel':u'Close',\n",
    "                    'xlabel':u'日期',\n",
    "                    'xticks':20,\n",
    "                    'xticklabels':'%Y-%m-%d'\n",
    "                   }\n",
    "    app.fig_output(**layout_dict)\n",
    "\n",
    "def log_trade_info(stock_dat):\n",
    "    signal_shift = stock_dat.Signal.shift(1)\n",
    "    # 序列最前面的NaN值用-1填充\n",
    "    signal_shift.fillna(value=-1, inplace=True)\n",
    "    list_signal = np.sign(stock_dat.Signal - signal_shift)\n",
    "\n",
    "    buy_signal = stock_dat[list_signal.isin([1])]\n",
    "    sell_signal = stock_dat[list_signal.isin([-1])]\n",
    "\n",
    "    trade_info = pd.DataFrame({'BuyTime':buy_signal.index.strftime(\"%y.%m.%d\"),\n",
    "                              'SellTime':sell_signal.index.strftime(\"%y.%m.%d\"),\n",
    "                              'BuyPrice':buy_signal.Close.values,\n",
    "                              'SellPrice':sell_signal.Close.values})\n",
    "    trade_info['DiffPrice'] = trade_info.SellPrice - trade_info.BuyPrice\n",
    "    trade_info['PctProfit'] = np.round(trade_info.DiffPrice/trade_info.BuyPrice*100,2)\n",
    "\n",
    "    win_count = (trade_info.DiffPrice >= 0).sum()\n",
    "    loss_count = (trade_info.DiffPrice < 0).sum()\n",
    "    win_profit = trade_info[trade_info.PctProfit >= 0].PctProfit.sum()\n",
    "    loss_profit = trade_info[trade_info.PctProfit < 0]\n",
    "\n",
    "    # 临时把标准输出重定向到一个文件，然后再恢复正常\n",
    "    with open('logtrade.txt','w') as f:\n",
    "        oldstdout = sys.stdout\n",
    "        sys.stdout = f\n",
    "        try:\n",
    "            print(trade_info)\n",
    "            print(f'loss_count:{loss_count},win_count:{win_count},ratio:{round(win_count/(win_count + loss_count),2)}%')\n",
    "            print(f'average loss:{round((loss_profit / loss_count),2)} %average win:{round((win_profit/win_count),2)}%')\n",
    "        finally:\n",
    "            sys.stdout = oldstdout\n",
    "\n",
    "\n",
    "def draw_absolute_profit(stock_dat):\n",
    "    cash_init = 100000 # 初始资金\n",
    "    cash_hold = 100000 # 初始资金\n",
    "    posit_num = 0 # 持股数目\n",
    "    skip_days = False # 持股/持币状态\n",
    "    slippage = 0.01 #滑点，默认0.01\n",
    "    c_rate = 5.0 / 10000 # 手续费,commission,默认为万分之5\n",
    "    t_rate = 1.0 / 1000 #印花税,tax,默认千分之1\n",
    "\n",
    "    # 绝对收益-资金的度量\n",
    "    for k1_index, today in stock_dat.iterrows():\n",
    "        # 买入 卖出执行代码\n",
    "        if today.Signal == 1 and skip_days == False: # 买入\n",
    "            skip_days = True\n",
    "            posit_num = int(cash_hold / (today.Close + slippage)) # 资金转换为股票\n",
    "            posit_num = int(posit_num / 100)* 100 # 买入股票最少100股，对posit_num向下兼容\n",
    "            buy_cash = posit_num * (today.Close + slippage) #计算买入股票所需现金\n",
    "            # 计算手续费，不足5元按5元收，并保留2位小数\n",
    "            commission = round(max(buy_cash * c_rate,5),2)\n",
    "            cash_hold = cash_hold - buy_cash - commission\n",
    "        elif today.Signal == -1 and skip_days == True: #卖出，避免未买先卖\n",
    "            skip_days = False\n",
    "            # 计算卖出股票得到现金，卖出股票可以不是整百\n",
    "            sell_cash = posit_num * (today.Close - slippage)\n",
    "            # 计算手续费，不足5按5元收，并保留2位小数\n",
    "            commission = round(max(sell_cash * c_rate, 5),2)\n",
    "            # 计算印花税，保留2位小数\n",
    "            tax = round(sell_cash * t_rate, 2)\n",
    "            # 剩余现金\n",
    "            cash_hold = cash_hold + sell_cash - commission - tax\n",
    "        if skip_days == True: #持股\n",
    "            stock_dat.loc[k1_index,'total'] = posit_num * today.Close + cash_hold\n",
    "        else:# 空仓\n",
    "            stock_dat.loc[k1_index,'total'] = cash_hold\n",
    "    line_key = \"posit %d;up %.2f%%\" % (stock_dat['total'].iloc[-1],(stock_dat['total'].iloc[-1] - cash_init) / cash_init * 100)\n",
    "    print(line_key)\n",
    "            \n",
    "    layout_dict = {'figsize':(14 ,7),\n",
    "                   'index':stock_dat.index,\n",
    "                   'draw_kind':{\n",
    "                       'line':{\n",
    "                           line_key:stock_dat.total\n",
    "                       }},\n",
    "                    'title':u'600111 交易收益',\n",
    "                    'ylabel':u'Close',\n",
    "                    'xlabel':u'日期',\n",
    "                    'xticks':20,\n",
    "                    'xticklabels':'%Y-%m-%d'\n",
    "                   }\n",
    "    app.fig_output(**layout_dict)\n",
    "\n",
    "def draw_relative_profit(stock_dat):\n",
    "    # 相对收益-策略 VS 基准\n",
    "    stock_dat['benchmark_profit_log'] = np.log(stock_dat.Close/stock_dat.Close.shift(1))\n",
    "    # -1用0代替，表示没有收益\n",
    "    stock_dat.loc[stock_dat.Signal == -1, 'Signal'] = 0\n",
    "    stock_dat['trend_profit_log'] = stock_dat['Signal'] * stock_dat.benchmark_profit_log\n",
    "    line_trend_key = \"trend profit%.2f\" % (stock_dat['trend_profit_log'].cumsum().iloc[-1])\n",
    "    line_bench_key = \"bench profit%.2f\" % (stock_dat['benchmark_profit_log'].cumsum().iloc[-1])\n",
    "    layout_dict = {\n",
    "        'figsize':(14,5),\n",
    "        'index':stock_dat.index,\n",
    "        'draw_kind':{\n",
    "            'line':{\n",
    "                line_bench_key:stock_dat['benchmark_profit_log'].cumsum(),\n",
    "                line_trend_key:stock_dat['trend_profit_log'].cumsum()\n",
    "            }\n",
    "        },\n",
    "        'title':u'600111 相对收益率',\n",
    "        'ylabel':u'相对收益率',\n",
    "        'xlabel':u\"日期\",\n",
    "        'xticks':20,\n",
    "        'legend':u'best',\n",
    "        'xticklabels':'%Y-%m-%d'\n",
    "    }\n",
    "    app.fig_output(**layout_dict)\n",
    "\n",
    "def draw_closemax_risk(stock_dat):\n",
    "    # 度量策略最大风险回撤-收盘价最大回撤\n",
    "    # 计算收盘价曲线当前的滚动最高值\n",
    "    stock_dat['max_close'] = stock_dat['Close'].expanding().max()\n",
    "    # 计算收盘价曲线在滚动最高值之后所回撤的百分比\n",
    "    stock_dat['per_close'] = stock_dat['Close'] / stock_dat['max_close']\n",
    "\n",
    "    # 找出收盘价的最大回撤率交易日\n",
    "    min_point_df = stock_dat.sort_values(by=['per_close'])[0:1]\n",
    "    min_point_close = min_point_df.per_close\n",
    "    # 找出收盘价的最大回撤率所对应的最高值交易日和最大回撤交易日，并打印显示\n",
    "    max_point_df = stock_dat[stock_dat.index <= min_point_close.index[0]].sort_values(by=['Close'], ascending=False)[0:1]\n",
    "    max_point_close = max_point_df.Close\n",
    "    print(\"股价最大回撤%5.2f%% 从%s开始从%s结束\" % ((1 - min_point_close.values[0]) * 100,max_point_close.index[0], min_point_close.index[0]))\n",
    "    ## 最大股价回撤 29.21% 从2018-06-12 00:00:00 开始至2018-12-27 00:00:00结束\n",
    "    layout_dict = {\n",
    "        'figsize':(14,5),\n",
    "        'index':stock_dat.index,\n",
    "        'draw_kind':{\n",
    "            'line':\n",
    "            {\n",
    "                '最大收盘价':stock_dat.max_close,\n",
    "                '收盘价':stock_dat.Close\n",
    "            },\n",
    "            'annotate':\n",
    "            {\n",
    "                u\"股价最大回撤\\n{}\".format(1 - min_point_close.values[0]):\n",
    "                {\n",
    "                    'andata':min_point_df,\n",
    "                    'va':'top',\n",
    "                    'xy_y':'Close',\n",
    "                    'xytext':(0, stock_dat['High'].mean()),\n",
    "                    'fontsize':8,\n",
    "                    'arrow':dict(facecolor='green',shrink=0.1)\n",
    "                },\n",
    "            }\n",
    "        },\n",
    "        'title':u\"600111 收盘价最大回撤\",\n",
    "        'ylabel':u\"收盘价最大回撤\",\n",
    "        'xlabel':u\"日期\",\n",
    "        'xticks':20,\n",
    "        'legend':u'best',\n",
    "        'xticklabels':'%Y-%m-%d'\n",
    "    }\n",
    "    app.fig_output(**layout_dict)\n",
    "\n",
    "def draw_profitmax_risk(stock_dat):\n",
    "    # 度量策略最大风险回撤\n",
    "    cash_hold = 100000 #初始资金\n",
    "    posit_num = 0 #持股数目\n",
    "    skip_days = False # 持股/持币状态\n",
    "    slippage = 0.01 # 滑点，默认为0.0.1\n",
    "    c_rate = 5.0 / 10000 #手续费,commission，默认万分之5\n",
    "    t_rate = 1.0 / 1000 #印花税，tax 默认千分之一\n",
    "    # 绝对收益-资金的度量\n",
    "    for k1_index, today in stock_dat.iterrows():\n",
    "        # 买入/卖出执行代码\n",
    "        if today.Signal == 1 and skip_days == False: #买入\n",
    "            skip_days = True\n",
    "            # 资金转化为股票\n",
    "            posit_num = int(cash_hold / (today.Close +slippage))\n",
    "            posit_num = int(posit_num / 100) * 100\n",
    "            # 计算买入股票所需现金\n",
    "            buy_cash = posit_num * (today.Close + slippage)\n",
    "            # 计算手续费，不足5元按5元收，并保留2位小数\n",
    "            commission = round(max(buy_cash *c_rate,5),2)\n",
    "            cash_hold = cash_hold - buy_cash - commission\n",
    "        elif today.Signal == -1 and skip_days == True: #卖出 避免未买先卖\n",
    "            skip_days = False\n",
    "            sell_cash = posit_num * (today.Close - slippage) # 计算卖出股票得到的现金 卖出股票可以不是整百\n",
    "            # 计算手续费：不足5元按5元收，并保留2位小数\n",
    "            commission = round(max(sell_cash * c_rate,5),2)\n",
    "            # 计算印花税，保留2位小数\n",
    "            tax = round(sell_cash * t_rate, 2)\n",
    "            # 剩余现金\n",
    "            cash_hold = cash_hold + sell_cash - commission - tax\n",
    "        if skip_days == True: # 持股\n",
    "            stock_dat.loc[k1_index,'total'] = posit_num * today.Close + cash_hold\n",
    "        else: # 空仓\n",
    "            stock_dat.loc[k1_index,'total'] = cash_hold\n",
    "        # expanding() 计算资金曲线当前的滚动最高值\n",
    "        stock_dat[\"max_total\"] = stock_dat['total'].expanding().max()\n",
    "        # 计算资金曲线在滚动最高值之后所回撤的百分比\n",
    "        stock_dat['per_total'] = stock_dat['total'] / stock_dat['max_total']\n",
    "    \n",
    "    min_point_df = stock_dat.sort_values(by = ['per_total'])[0:1]\n",
    "    min_point_total = min_point_df.per_total\n",
    "    max_point_df = stock_dat[stock_dat.index <= min_point_total.index[0]].sort_values(by = ['total'], ascending = False)[0:1]\n",
    "    max_point_total = max_point_df.total\n",
    "\n",
    "    print(\"资金最大回撤%5.2f%% 从%s开始至%s结束\" % ((1 - min_point_total.values[0]) * 100, max_point_total.index[0], min_point_total.index[0]))\n",
    "    layout_dict = {\n",
    "        'figsize': (14, 5),\n",
    "        'index': stock_dat.index,\n",
    "        'draw_kind': {\n",
    "            'line':\n",
    "                {\n",
    "                    '最大资金':stock_dat.max_total,\n",
    "                    '资金':stock_dat.total\n",
    "                },\n",
    "            'annotate':{\n",
    "                    u\"资金最大回撤\\n{}\".format(1 - min_point_total.values[0]):\n",
    "                    {\n",
    "                        'andata': min_point_df,\n",
    "                        'va':'top',\n",
    "                        'xy_y':'total',\n",
    "                        'xytext':(0, stock_dat['High'].mean()),\n",
    "                        'fontsize':8,\n",
    "                        'arrow':dict(facecolor='green',shrink=0.1)\n",
    "                    },\n",
    "            }},\n",
    "        'title':u\"资金最大回撤\",\n",
    "        'ylabel':u\"资金最大回撤\",\n",
    "        'xlabel':u'日期',\n",
    "        'xticks':20,\n",
    "        'legend':u'best'\n",
    "    }\n",
    "    app.fig_output(**layout_dict)\n",
    "\n",
    "def draw_attr_chart(stock_dat):\n",
    "    stock_dat['atr14'] = talib.ATR(stock_dat.High.values,stock_dat.Low.values,stock_dat.Close.values,timeperiod=14) #计算ATR14\n",
    "    stock_dat['atr21'] = talib.ATR(stock_dat.High.values,stock_dat.Low.values,stock_dat.Close.values, timeperiod=21) #计算ATR21\n",
    "    layout_dict = {\n",
    "        'figsize':(14, 5),\n",
    "        'index':stock_dat.index,\n",
    "        'draw_kind': {\n",
    "            'line': {\n",
    "                'str14': stock_dat.atr14,\n",
    "                'str21': stock_dat.atr21\n",
    "            },\n",
    "        },\n",
    "            'title':u'ATR',\n",
    "            'ylabel':u\"波动幅度\",\n",
    "            'xlabel':u\"日期\",\n",
    "            'xticks': 15,\n",
    "            'legend': u'best',\n",
    "            'xticklabels':'%Y-Ym-%d' #strftime\n",
    "        }\n",
    "    \n",
    "    app.fig_output(**layout_dict)\n",
    "\n",
    "df_stockload = bs_k_data_stock('sh.600111','2025-01-01', '2025-08-26')\n",
    "df_stockload2 = get_trade_signal(df_stockload)\n",
    "draw_trade_chart(df_stockload2)\n",
    "log_trade_info(df_stockload2)\n",
    "draw_absolute_profit(df_stockload2)\n",
    "draw_relative_profit(df_stockload2)\n",
    "draw_closemax_risk(df_stockload2)\n",
    "draw_profitmax_risk(df_stockload2)\n",
    "draw_attr_chart(df_stockload2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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